Refined entropy coding for level maps

ABSTRACT

An apparatus for decoding a current block includes a processor that is configured to obtain a transform class of a transform type used for decoding a transform block of the current block; select, based on the transform class, a template for coding a value related to a transform coefficient at a row and a column of the transform block; obtain, using the template, an index of a probability distribution in a table of probability distributions; and decode, from a compressed bitstream, the value using the probability distribution.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation of U.S. application patent Ser. No.16/659,666, filed Oct. 22, 2019, which is a continuation of U.S.application patent Ser. No. 15/798,495, filed Oct. 31, 2017, whichclaims priority to and the benefit of U.S. Provisional ApplicationPatent Ser. No. 62/575,716, filed Oct. 23, 2017, the entire disclosuresof which are hereby incorporated by reference.

BACKGROUND

Digital video streams may represent video using a sequence of frames orstill images. Digital video can be used for various applicationsincluding, for example, video conferencing, high definition videoentertainment, video advertisements, or sharing of user-generatedvideos. A digital video stream can contain a large amount of data andconsume a significant amount of computing or communication resources ofa computing device for processing, transmission, or storage of the videodata. Various approaches have been proposed to reduce the amount of datain video streams, including compression and other encoding techniques.

SUMMARY

A first aspect is an apparatus for decoding a current block. Theapparatus includes a processor that is configured to obtain a transformclass of a transform type used for decoding a transform block of thecurrent block; select, based on the transform class, a template forcoding a value related to a transform coefficient at a row and a columnof the transform block; obtain, using the template, an index of aprobability distribution in a table of probability distributions; anddecode, from a compressed bitstream, the value using the probabilitydistribution.

A second aspect is a method for coding a current block. The methodincludes obtaining a transform class of a transform type used fordecoding a transform block of the current block; selecting, based on thetransform class, a template for coding a value related to a transformcoefficient at a row and a column of the transform block; obtaining,using the template, an index of a probability distribution in a table ofprobability distributions; and coding the value using the probabilitydistribution.

A third aspect is a non-transitory computer-readable storage medium thatincludes executable instructions that, when executed, facilitateperformance of operations for coding a current block. The operationsinclude operations to obtain a transform class of a transform type usedfor decoding a transform block of the current block; select, based onthe transform class, a template for coding a value related to atransform coefficient at a row and a column of the transform block;obtain, using the template, an index of a probability distribution in atable of probability distributions; and decode, from a compressedbitstream, the value using the probability distribution. The transformclass can be one of a vertical transform class, a horizontal transformclass, or a 2-dimensional transform class.

These and other aspects of the present disclosure are disclosed in thefollowing detailed description of the embodiments, the appended claimsand the accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

The description herein makes reference to the accompanying drawingswherein like reference numerals refer to like parts throughout theseveral views.

FIG. 1 is a schematic of a video encoding and decoding system.

FIG. 2 is a block diagram of an example of a computing device that canimplement a transmitting station or a receiving station.

FIG. 3 is a diagram of a video stream to be encoded and subsequentlydecoded.

FIG. 4 is a block diagram of an encoder according to implementations ofthis disclosure.

FIG. 5 is a block diagram of a decoder according to implementations ofthis disclosure.

FIG. 6 is a flowchart diagram of a process for encoding a transformblock in an encoded video bitstream using level maps according to animplementation of this disclosure.

FIG. 7 is a diagram illustrating the stages of transform coefficientcoding using level maps in accordance with implementations of thisdisclosure.

FIG. 8 is a diagram of previously coded neighbors in a non-zero mapaccording to an implementation of this disclosure.

FIG. 9 is a flowchart diagram of a process for coding a transform blockusing level maps according to an implementation of this disclosure.

FIGS. 10A-B is a diagram of examples of templates for determining acoding context according to implementations of this disclosure.

FIG. 11 is a diagram of a coefficient token tree that can be used toentropy code transform blocks according to implementations of thisdisclosure.

FIG. 12 is a flowchart diagram of a process for coding a transform blockusing a coefficient alphabet including head tokens and tail tokensaccording to an implementation of this disclosure.

FIG. 13 is a diagram of examples of probability mappings according toimplementations of this disclosure.

FIG. 14 is a diagram of examples of intra prediction modes according toimplementations of this disclosure.

FIG. 15 is a flowchart diagram of a process for intra-coding a currentblock according to an implementation of this disclosure.

FIG. 16 is a diagram of examples of regions for determining a contextaccording to implementations of this disclosure.

FIG. 17 is a flowchart diagram of a process for decoding a transformblock using level maps according to an implementation of thisdisclosure.

DETAILED DESCRIPTION

As mentioned above, compression schemes related to coding video streamsmay include breaking images into blocks and generating a digital videooutput bitstream (i.e., an encoded bitstream) using one or moretechniques to limit the information included in the output bitstream. Areceived bitstream can be decoded to re-create the blocks and the sourceimages from the limited information. Encoding a video stream, or aportion thereof, such as a frame or a block, can include using temporalor spatial similarities in the video stream to improve codingefficiency. For example, a current block of a video stream may beencoded based on identifying a difference (residual) between thepreviously coded pixel values, or between a combination of previouslycoded pixel values, and those in the current block.

Encoding using spatial similarities can be known as intra prediction.Intra prediction attempts to predict the pixel values of a block of aframe of video using pixels peripheral to the block; that is, usingpixels that are in the same frame as the block but that are outside theblock. A prediction block resulting from intra prediction is referred toherein as an intra predictor. Intra prediction can be performed along adirection of prediction where each direction can correspond to an intraprediction mode. The intra prediction mode can be signalled by anencoder to a decoder.

Encoding using temporal similarities can be known as inter prediction.Inter prediction attempts to predict the pixel values of a block using apossibly displaced block or blocks from a temporally nearby frame (i.e.,reference frame) or frames. A temporally nearby frame is a frame thatappears earlier or later in time in the video stream than the frame ofthe block being encoded. A prediction block resulting from interprediction is referred to herein as inter predictor.

Inter prediction is performed using a motion vector. A motion vectorused to generate a prediction block refers to a frame other than acurrent frame, i.e., a reference frame. Reference frames can be locatedbefore or after the current frame in the sequence of the video stream.Some codecs use up to eight reference frames, which can be stored in aframe buffer. The motion vector can refer to (i.e., use) one of thereference frames of the frame buffer. As such, one or more referenceframes can be available for coding a current frame.

As mentioned above, a current block of a video stream may be encodedbased on identifying a difference (residual) between the previouslycoded pixel values and those in the current block. In this way, only theresidual and parameters used to generate the residual need be added tothe encoded bitstream. The residual may be encoded using a lossyquantization step.

The residual block can be in the pixel domain. The residual block can betransformed into the frequency domain resulting in a transform block oftransform coefficients. The transform coefficients can be quantizedresulting into a quantized transform block of quantized transformcoefficients. The quantized coefficients can be entropy encoded andadded to an encoded bitstream. A decoder can receive the encodedbitstream, entropy decode the quantized transform coefficients toreconstruct the original video frame.

Entropy coding is a technique for “lossless” coding that relies uponprobability models that model the distribution of values occurring in anencoded video bitstream. By using probability models based on a measuredor estimated distribution of values, entropy coding can reduce thenumber of bits required to represent video data close to a theoreticalminimum. In practice, the actual reduction in the number of bitsrequired to represent video data can be a function of the accuracy ofthe probability model, the number of bits over which the coding isperformed, and the computational accuracy of fixed-point arithmetic usedto perform the coding.

In an encoded video bitstream, many of the bits are used for one of twothings: either content prediction (e.g., inter mode/motion vectorcoding, intra prediction mode coding, etc.) or residual coding (e.g.,transform coefficients).

With respect to content prediction, the bits in the bitstream caninclude, for a block, the intra prediction mode used to encode theblock. The intra prediction mode can be coded (encoded by an encoder anddecoded by a decoder) using entropy coding. As such, a context isdetermined for the intra prediction mode and a probability model,corresponding to the context, for coding the intra prediction mode isused for the coding.

Encoders may use techniques to decrease the amount of bits spent oncoefficient coding. For example, a coefficient token tree (which mayalso be referred to as a binary token tree) specifies the scope of thevalue, with forward-adaptive probabilities for each branch in this tokentree. The token base value is subtracted from the value to be coded toform a residual then the block is coded with fixed probabilities. Asimilar scheme with minor variations including backward-adaptivity isalso possible. Adaptive techniques can alter the probability models asthe video stream is being encoded to adapt to changing characteristicsof the data. In any event, a decoder is informed of (or has available)the probability model used to encode an entropy-coded video bitstream inorder to decode the video bitstream.

As described above, entropy coding a sequence of symbols is typicallyachieved by using a probability model to determine a probability p forthe sequence and then using binary arithmetic coding to map the sequenceto a binary codeword at the encoder and to decode that sequence from thebinary codeword at the decoder. The length (i.e., number of bits) of thecodeword is given by −log(p). The efficiency of entropy coding can bedirectly related to the probability model. Throughout this document, logdenotes the logarithm function to base two (2) unless specifiedotherwise.

A model, as used herein, can be, or can be a parameter in, a lossless(entropy) coding. A model can be any parameter or method that affectsprobability estimation for entropy coding.

A purpose of context modeling is to obtain probability distributions fora subsequent entropy coding engine, such as arithmetic coding, Huffmancoding, and other variable-length-to-variable-length coding engines. Toachieve good compression performance, a large number of contexts may berequired. For example, some video coding systems can include hundreds oreven thousands of contexts for transform coefficient coding alone. Eachcontext can correspond to a probability distribution.

A probability distribution can be learnt by a decoder and/or included inthe header of a frame to be decoded.

Learnt can mean that an entropy coding engine of a decoder can adapt theprobability distributions (i.e., probability models) of a context modelbased on decoded frames. For example, the decoder can have available aninitial probability distribution that the decoder (e.g., the entropycoding engine of the decoder) can continuously update as the decoderdecodes additional frames. The updating of the probability models caninsure that the initial probability distribution is updated to reflectthe actual distributions in the decoded frames.

Including a probability distribution in the header can instruct thedecoder to use the included probability distribution for decoding thenext frame, given the corresponding context. A cost (in bits) isassociated with including each probability distribution in the header.For example, in a coding system that includes 3000 contexts and thatencodes a probability distribution (coded as an integer value between 1and 255) using 8 bits, 24,000 bits are added to the encoded bitstream.These bits are overhead bits. Some techniques can be used to reduce thenumber of overhead bits. For example, the probability distributions forsome, but not all, of the contexts can be included. For example,prediction schemes can also be used to reduce the overhead bits. Evenwith these overhead reduction techniques, the overhead is non-zero.

As already mentioned, residuals for a block of video are transformedinto transform blocks of transform coefficients. The transform blocksare in the frequency domain and one or more transform blocks may begenerated for a block of video. The transform coefficients are quantizedand entropy coded into an encoded video bitstream. A decoder uses theencoded transform coefficients and the reference frames to reconstructthe block. Entropy coding a transform coefficient involves the selectionof a context model (also referred to as probability context model orprobability model) which provides estimates of conditional probabilitiesfor coding the binary symbols of a binarized transform coefficient.

Implementations of this disclosure can result in reduced numbers ofcontexts for coding different aspects of content prediction and/orresidual coding. Implementations of this disclosure can reduce thenumber of probability values associated with a context. As suchimplementations of this disclosure can have reduced computational andstorage complexity without adversely affecting compression performance.

Refined entropy coding is described herein first with reference to asystem in which the teachings may be incorporated.

FIG. 1 is a schematic of a video encoding and decoding system 100. Atransmitting station 102 can be, for example, a computer having aninternal configuration of hardware such as that described in FIG. 2.However, other suitable implementations of the transmitting station 102are possible. For example, the processing of the transmitting station102 can be distributed among multiple devices.

A network 104 can connect the transmitting station 102 and a receivingstation 106 for encoding and decoding of the video stream. Specifically,the video stream can be encoded in the transmitting station 102 and theencoded video stream can be decoded in the receiving station 106. Thenetwork 104 can be, for example, the Internet. The network 104 can alsobe a local area network (LAN), wide area network (WAN), virtual privatenetwork (VPN), cellular telephone network or any other means oftransferring the video stream from the transmitting station 102 to, inthis example, the receiving station 106.

The receiving station 106, in one example, can be a computer having aninternal configuration of hardware such as that described in FIG. 2.However, other suitable implementations of the receiving station 106 arepossible. For example, the processing of the receiving station 106 canbe distributed among multiple devices.

Other implementations of the video encoding and decoding system 100 arepossible. For example, an implementation can omit the network 104. Inanother implementation, a video stream can be encoded and then storedfor transmission at a later time to the receiving station 106 or anyother device having memory. In one implementation, the receiving station106 receives (e.g., via the network 104, a computer bus, and/or somecommunication pathway) the encoded video stream and stores the videostream for later decoding. In an example implementation, a real-timetransport protocol (RTP) is used for transmission of the encoded videoover the network 104. In another implementation, a transport protocolother than RTP may be used, e.g., an HTTP-based video streamingprotocol.

When used in a video conferencing system, for example, the transmittingstation 102 and/or the receiving station 106 may include the ability toboth encode and decode a video stream as described below. For example,the receiving station 106 could be a video conference participant whoreceives an encoded video bitstream from a video conference server(e.g., the transmitting station 102) to decode and view and furtherencodes and transmits its own video bitstream to the video conferenceserver for decoding and viewing by other participants.

FIG. 2 is a block diagram of an example of a computing device 200 thatcan implement a transmitting station or a receiving station. Forexample, the computing device 200 can implement one or both of thetransmitting station 102 and the receiving station 106 of FIG. 1. Thecomputing device 200 can be in the form of a computing system includingmultiple computing devices, or in the form of a single computing device,for example, a mobile phone, a tablet computer, a laptop computer, anotebook computer, a desktop computer, and the like.

A CPU 202 in the computing device 200 can be a central processing unit.Alternatively, the CPU 202 can be any other type of device, or multipledevices, capable of manipulating or processing information now-existingor hereafter developed. Although the disclosed implementations can bepracticed with a single processor as shown, e.g., the CPU 202,advantages in speed and efficiency can be achieved using more than oneprocessor.

A memory 204 in the computing device 200 can be a read-only memory (ROM)device or a random access memory (RAM) device in an implementation. Anyother suitable type of storage device can be used as the memory 204. Thememory 204 can include code and data 206 that is accessed by the CPU 202using a bus 212. The memory 204 can further include an operating system208 and application programs 210, the application programs 210 includingat least one program that permits the CPU 202 to perform the methodsdescribed here. For example, the application programs 210 can includeapplications 1 through N, which further include a video codingapplication that performs the methods described here. The computingdevice 200 can also include a secondary storage 214, which can, forexample, be a memory card used with a computing device 200 that ismobile. Because the video communication sessions may contain asignificant amount of information, they can be stored in whole or inpart in the secondary storage 214 and loaded into the memory 204 asneeded for processing.

The computing device 200 can also include one or more output devices,such as a display 218. The display 218 may be, in one example, a touchsensitive display that combines a display with a touch sensitive elementthat is operable to sense touch inputs. The display 218 can be coupledto the CPU 202 via the bus 212. Other output devices that permit a userto program or otherwise use the computing device 200 can be provided inaddition to or as an alternative to the display 218. When the outputdevice is or includes a display, the display can be implemented invarious ways, including by a liquid crystal display (LCD), a cathode-raytube (CRT) display or light emitting diode (LED) display, such as anorganic LED (OLED) display.

The computing device 200 can also include or be in communication with animage-sensing device 220, for example a camera, or any otherimage-sensing device 220 now existing or hereafter developed that cansense an image such as the image of a user operating the computingdevice 200. The image-sensing device 220 can be positioned such that itis directed toward the user operating the computing device 200. In anexample, the position and optical axis of the image-sensing device 220can be configured such that the field of vision includes an area that isdirectly adjacent to the display 218 and from which the display 218 isvisible.

The computing device 200 can also include or be in communication with asound-sensing device 222, for example a microphone, or any othersound-sensing device now existing or hereafter developed that can sensesounds near the computing device 200. The sound-sensing device 222 canbe positioned such that it is directed toward the user operating thecomputing device 200 and can be configured to receive sounds, forexample, speech or other utterances, made by the user while the useroperates the computing device 200.

Although FIG. 2 depicts the CPU 202 and the memory 204 of the computingdevice 200 as being integrated into a single unit, other configurationscan be utilized. The operations of the CPU 202 can be distributed acrossmultiple machines (each machine having one or more of processors) thatcan be coupled directly or across a local area or other network. Thememory 204 can be distributed across multiple machines such as anetwork-based memory or memory in multiple machines performing theoperations of the computing device 200. Although depicted here as asingle bus, the bus 212 of the computing device 200 can be composed ofmultiple buses. Further, the secondary storage 214 can be directlycoupled to the other components of the computing device 200 or can beaccessed via a network and can comprise a single integrated unit such asa memory card or multiple units such as multiple memory cards. Thecomputing device 200 can thus be implemented in a wide variety ofconfigurations.

FIG. 3 is a diagram of an example of a video stream 300 to be encodedand subsequently decoded. The video stream 300 includes a video sequence302. At the next level, the video sequence 302 includes a number ofadjacent frames 304. While three frames are depicted as the adjacentframes 304, the video sequence 302 can include any number of adjacentframes 304. The adjacent frames 304 can then be further subdivided intoindividual frames, e.g., a frame 306. At the next level, the frame 306can be divided into a series of segments 308 or planes. The segments 308can be subsets of frames that permit parallel processing, for example.The segments 308 can also be subsets of frames that can separate thevideo data into separate colors. For example, the frame 306 of colorvideo data can include a luminance plane and two chrominance planes. Thesegments 308 may be sampled at different resolutions.

Whether or not the frame 306 is divided into the segments 308, the frame306 may be further subdivided into blocks 310, which can contain datacorresponding to, for example, 16×16 pixels in the frame 306. The blocks310 can also be arranged to include data from one or more segments 308of pixel data. The blocks 310 can also be of any other suitable sizesuch as 4×4 pixels, 8×8 pixels, 16×8 pixels, 8×16 pixels, 16×16 pixelsor larger.

FIG. 4 is a block diagram of an encoder 400 in accordance withimplementations of this disclosure. The encoder 400 can be implemented,as described above, in the transmitting station 102 such as by providinga computer software program stored in memory, for example, the memory204. The computer software program can include machine instructionsthat, when executed by a processor such as the CPU 202, cause thetransmitting station 102 to encode video data in manners describedherein. The encoder 400 can also be implemented as specialized hardwareincluded in, for example, the transmitting station 102. The encoder 400has the following stages to perform the various functions in a forwardpath (shown by the solid connection lines) to produce an encoded orcompressed bitstream 420 using the video stream 300 as input: anintra/inter prediction stage 402, a transform stage 404, a quantizationstage 406, and an entropy encoding stage 408. The encoder 400 may alsoinclude a reconstruction path (shown by the dotted connection lines) toreconstruct a frame for encoding of future blocks. In FIG. 4, theencoder 400 has the following stages to perform the various functions inthe reconstruction path: a dequantization stage 410, an inversetransform stage 412, a reconstruction stage 414, and a loop filteringstage 416. Other structural variations of the encoder 400 can be used toencode the video stream 300.

When the video stream 300 is presented for encoding, the frame 306 canbe processed in units of blocks. At the intra/inter prediction stage402, a block can be encoded using intra-frame prediction (also calledintra-prediction) or inter-frame prediction (also calledinter-prediction), or a combination of both. In any case, a predictionblock can be formed. In the case of intra-prediction, all or a part of aprediction block may be formed from samples in the current frame thathave been previously encoded and reconstructed. In the case ofinter-prediction, all or part of a prediction block may be formed fromsamples in one or more previously constructed reference framesdetermined using motion vectors.

Next, still referring to FIG. 4, the prediction block can be subtractedfrom the current block at the intra/inter prediction stage 402 toproduce a residual block (also called a residual). The transform stage404 transforms the residual into transform coefficients in, for example,the frequency domain using block-based transforms. Such block-basedtransforms include, for example, the Discrete Cosine Transform (DCT) andthe Asymmetric Discrete Sine Transform (ADST). Other block-basedtransforms are possible. Further, combinations of different transformsmay be applied to a single residual. In one example of application of atransform, the DCT transforms the residual block into the frequencydomain where the transform coefficient values are based on spatialfrequency. The lowest frequency (DC) coefficient at the top-left of thematrix and the highest frequency coefficient at the bottom-right of thematrix. It is worth noting that the size of a prediction block, andhence the resulting residual block, may be different from the size ofthe transform block. For example, the prediction block may be split intosmaller blocks to which separate transforms are applied.

The quantization stage 406 converts the transform coefficients intodiscrete quantum values, which are referred to as quantized transformcoefficients, using a quantizer value or a quantization level. Forexample, the transform coefficients may be divided by the quantizervalue and truncated. The quantized transform coefficients are thenentropy encoded by the entropy encoding stage 408. Entropy coding may beperformed using any number of techniques, including token and binarytrees. The entropy-encoded coefficients, together with other informationused to decode the block, which may include for example the type ofprediction used, transform type, motion vectors and quantizer value, arethen output to the compressed bitstream 420. The information to decodethe block may be entropy coded into block, frame, slice and/or sectionheaders within the compressed bitstream 420. The compressed bitstream420 can also be referred to as an encoded video stream or encoded videobitstream, and the terms will be used interchangeably herein.

The reconstruction path in FIG. 4 (shown by the dotted connection lines)can be used to ensure that both the encoder 400 and a decoder 500(described below) use the same reference frames and blocks to decode thecompressed bitstream 420. The reconstruction path performs functionsthat are similar to functions that take place during the decodingprocess that are discussed in more detail below, including dequantizingthe quantized transform coefficients at the dequantization stage 410 andinverse transforming the dequantized transform coefficients at theinverse transform stage 412 to produce a derivative residual block (alsocalled a derivative residual). At the reconstruction stage 414, theprediction block that was predicted at the intra/inter prediction stage402 can be added to the derivative residual to create a reconstructedblock. The loop filtering stage 416 can be applied to the reconstructedblock to reduce distortion such as blocking artifacts.

Other variations of the encoder 400 can be used to encode the compressedbitstream 420. For example, a non-transform based encoder 400 canquantize the residual signal directly without the transform stage 404for certain blocks or frames. In another implementation, an encoder 400can have the quantization stage 406 and the dequantization stage 410combined into a single stage.

FIG. 5 is a block diagram of a decoder 500 in accordance withimplementations of this disclosure. The decoder 500 can be implementedin the receiving station 106, for example, by providing a computersoftware program stored in the memory 204. The computer software programcan include machine instructions that, when executed by a processor suchas the CPU 202, cause the receiving station 106 to decode video data inthe manners described below. The decoder 500 can also be implemented inhardware included in, for example, the transmitting station 102 or thereceiving station 106.

The decoder 500, similar to the reconstruction path of the encoder 400discussed above, includes in one example the following stages to performvarious functions to produce an output video stream 516 from thecompressed bitstream 420: an entropy decoding stage 502, adequantization stage 504, an inverse transform stage 506, anintra/inter-prediction stage 508, a reconstruction stage 510, a loopfiltering stage 512 and a post filtering stage 514. Other structuralvariations of the decoder 500 can be used to decode the compressedbitstream 420.

When the compressed bitstream 420 is presented for decoding, the dataelements within the compressed bitstream 420 can be decoded by theentropy decoding stage 502 to produce a set of quantized transformcoefficients. The dequantization stage 504 dequantizes the quantizedtransform coefficients (e.g., by multiplying the quantized transformcoefficients by the quantizer value), and the inverse transform stage506 inverse transforms the dequantized transform coefficients using theselected transform type to produce a derivative residual that can beidentical to that created by the inverse transform stage 412 in theencoder 400. Using header information decoded from the compressedbitstream 420, the decoder 500 can use the intra/inter-prediction stage508 to create the same prediction block as was created in the encoder400, e.g., at the intra/inter prediction stage 402. At thereconstruction stage 510, the prediction block can be added to thederivative residual to create a reconstructed block. The loop filteringstage 512 can be applied to the reconstructed block to reduce blockingartifacts. Other filtering can be applied to the reconstructed block. Inan example, the post filtering stage 514 is applied to the reconstructedblock to reduce blocking distortion, and the result is output as anoutput video stream 516. The output video stream 516 can also bereferred to as a decoded video stream, and the terms will be usedinterchangeably herein.

Other variations of the decoder 500 can be used to decode the compressedbitstream 420. For example, the decoder 500 can produce the output videostream 516 without the post filtering stage 514. In some implementationsof the decoder 500, the post filtering stage 514 is applied after theloop filtering stage 512. The loop filtering stage 512 can include anoptional deblocking filtering stage. Additionally, or alternatively, theencoder 400 includes an optional deblocking filtering stage in the loopfiltering stage 416.

Some codecs may use level maps to code (i.e., encode by an encoder ordecode by a decoder) a transform block. That is, some codecs may uselevel maps to code the transform coefficients of the transform blocks.In level map coding, the transform block is decomposed into multiplelevel maps such that the level maps break down (i.e., reduce) the codingof each transform coefficient value into a series of binary decisionseach corresponding to a magnitude level (i.e., a map level). Thedecomposition can be done by using a multi-run process. As such, atransform coefficient of the transform block is decomposed into a seriesof level binaries and a residue according to the equation:

${{{coefficient}\lbrack r\rbrack}\lbrack c\rbrack} = {\left\{ {\left( {\sum\limits_{k = 0}^{T}{leve{{l_{k}\lbrack r\rbrack}\lbrack c\rbrack}}} \right) + {{{residue}\lbrack r\rbrack}\lbrack c\rbrack}} \right\}*{{{sign}\lbrack r\rbrack}\lbrack c\rbrack}}$Where residue[r][c] = absolute(coefficient[r][c]) − T − 1${{{sign}\lbrack r\rbrack}\lbrack c\rbrack} = \left\{ \begin{matrix}{{1\mspace{14mu} {if}\mspace{14mu} {{{coefficient}\lbrack r\rbrack}\lbrack c\rbrack}}\  > 0} \\{{{- 1}\mspace{14mu} {if}\mspace{14mu} {{{coefficient}\lbrack r\rbrack}\lbrack c\rbrack}}\  < 0}\end{matrix} \right.$

In the above equation, coefficient[r][c] is the transform coefficient ofthe transform block at the position (row=r, column=c), T is the maximummap level, level_(k) is the level map corresponding to map level k,residue is a coefficient residual map, and sign is the sign map of thetransform coefficients. These terms are further described below withrespect to FIG. 7. The transform coefficients of a transform block canbe re-composed using the same equation, such as by a decoder, fromencoded level_(k) maps, residual map residue, and sign map sign.

A zeroth run can be used to determine a non-zero map (also referred toas a level-0 map) which indicates which transform coefficients of thetransform block are zero and which are non-zero. Level mapscorresponding to runs 1 through a maximum (i.e., threshold) level T(i.e., level-1 map, level-2 map, . . . , level-T map) are generated inascending order from level 1 to the maximum map level T. The level mapfor level k, referred to as the level-k map, indicates which transformcoefficients of the transform block have absolute values greater to orequal to k. The level maps are binary maps. A final run generates acoefficients residue map. If the transform block contains transformcoefficient values above the maximum map level T, the coefficientsresidue map indicates the extent (i.e., residue) that these coefficientsare greater than the maximum map level T.

When generating (i.e., coding) the level-k map, only the positions (r,c) corresponding to positions (r, c) of the level-(k−1) map which areequal to 1 (i.e., level_(k-1)[r][c] =1) need be processed—otherpositions of the level-(k−1) are determined to be less than k and,therefore, there is no need to process them for the level-k map. Thisreduces processing complexity and reduces the amount of binary codingoperations.

As the level maps contain binary values, the above and left neighbors ofa value to be encoded are binary values. A context model based on thebinary values of any number of previously coded neighbors can bedetermined. The context model can fully utilize information from allthese neighbors. The previously coded neighbors can be neighbors in thesame level map or a preceding level map, such as an immediatelypreceding level map. The immediately preceding map of the level-k (e.g.,level-2) map is the level-(k-1) (e.g., level-1) map. Contexts accordingto this disclosure can be less complex thereby resulting in efficientmodels for coding the level maps.

When encoding a level-k map, the fully coded level-(k-1) map and thepartially coded level-k map can be used as context information forcontext modeling. As compared to transform coefficient coding of othervideo systems, which code one coefficient value at a time before movingto next transform coefficient, implementations of this disclosure canreduce the cardinality of the reference sample set. This is so because,as further described herein, the information from the level-(k−1) mapand partially coded level-k map are binary information. The binaryinformation enables the use of sophisticated spatial neighboringtemplates for context modeling binary information. Such spatialneighboring templates can better capture statistical characteristics oftransform blocks, especially those with larger transform block sizes.

FIG. 6 is a flowchart diagram of a process 600 for encoding a transformblock in an encoded video bitstream using level maps according to animplementation of this disclosure. The process 600 can be implemented inan encoder such as the encoder 400. The encoded video bitstream can bethe compressed bitstream 420 of FIG. 4.

The process 600 can be implemented, for example, as a software programthat can be executed by computing devices such as transmitting station102. The software program can include machine-readable instructions thatcan be stored in a memory such as the memory 204 or the secondarystorage 214, and that can be executed by a processor, such as CPU 202,to cause the computing device to perform the process 600. In at leastsome implementations, the process 600 can be performed in whole or inpart by the entropy encoding stage 408 of the encoder 400.

The process 600 can be implemented using specialized hardware orfirmware. Some computing devices can have multiple memories, multipleprocessors, or both. The steps or operations of the process 600 can bedistributed using different processors, memories, or both. Use of theterms “processor” or “memory” in the singular encompasses computingdevices that have one processor or one memory as well as devices thathave multiple processors or multiple memories that can be used in theperformance of some or all of the recited steps.

The process 600 is now explained with reference to FIG. 7. FIG. 7 is adiagram illustrating the stages 700 of transform coefficient codingusing level maps in accordance with implementations of this disclosure.FIG. 7 includes the zigzag forward scan direction 702, a transform block704, a non-zero map 706, a level-1 map 707, a level-2 map 709, anend-of-block map 726, a sign map 732, and a coefficient residual map734.

The process 600 can receive a transform block, such as the transformblock 704 of FIG. 7. The transform block can be received from thequantization step of an encoder, such as the quantization stage 406 ofthe encoder 400 of FIG. 4. The transform block 704 includes zero andnon-zero transform coefficients. Some of the non-zero coefficients maybe negative values.

At 602, a non-zero map is encoded. The non-zero map indicates positionsof the transform block that contain non-zero transform coefficients. Thenon-zero map can also be referred to as the level-0 map.

The non-zero map 706 of FIG. 6 illustrates a non-zero map. The non-zeromap can be generated by traversing the transform block 704 in a scandirection, such as the zigzag forward scan direction 702 of FIG. 7, andindicating in the non-zero map 706, using binary values, whether thecorresponding transform coefficient is a zero or a non-zero. In thenon-zero map 706, a non-zero transform coefficient of the transformblock 704 is indicated with the binary value 1 (one) and a zerotransform coefficient is indicated with the binary value 0 (zero).However, the indication can be reversed (i.e., a zero to indicate anon-zero transform coefficient and one (1) to indicate a zero transformcoefficient).

In an implementation, zero transform coefficients that are beyond (i.e.,come after) the last non-zero transform coefficient, based on the scandirection of the transform block, are not indicated in the non-zero map.For example, using the zigzag forward scan direction 702 to scan thetransform block 704, the last non-zero transform coefficient 708,corresponding to scan direction location 11, is the last indicatedtransform coefficient in the non-zero map 706 at last non-zerocoefficient 710. No values are indicated in the non-zero map 706 for thetransform coefficients corresponding to the scan positions 12-15 of thezigzag forward scan direction 702.

At 604, the process 600 encodes a respective lower-range level map. Eachlower-range map has a map level up to a maximum map level. A lower-rangelevel map indicates which values of the non-zero transform coefficientsare equal to the map level of the lower-range map and which values ofthe non-zero transform coefficients are greater than the map level.

For each map level k, up to the maximum map level T, a lower-range levelmap level_(k) is encoded. Each lower-range level map indicates whichvalues of the transform block are equal to the map level of thelower-range level map and which values of the transform block aregreater than the map level. As such, the process 600, using multipleruns (i.e., each run corresponding to a level k=1, 2, . . . , T), breaksdown the coding of transform coefficients into a series of binarydecisions each corresponding to a magnitude level. The binary decisionof a coefficient at row and column (r, c) in the transform block atlevel k can be defined by:

$\begin{matrix}{{{{level}_{r}\lbrack r\rbrack}\lbrack c\rbrack} = {{1\mspace{14mu} {if}\mspace{14mu} {{absolute}\left( {{{coefficient}\lbrack r\rbrack}\lbrack c\rbrack} \right)}} > k}} \\{= {{0\mspace{14mu} {if}\mspace{14mu} {{absolute}\left( {{{coefficient}\lbrack r\rbrack}\lbrack c\rbrack} \right)}} \leq k}}\end{matrix}$

For example, for k=1 (i.e., for the level-1 map 707), the process 600determines for each transform coefficient of the transform block 704whether the absolute value of the transform coefficient is greater thank (i.e., 1) or less than or equal to k. For the transform coefficient720 (i.e., at r=0, c=0), as the absolute value of −7 (i.e., |−7|=7) isgreater than 1, the process 600 sets the corresponding value 722 of thelevel-1 map 707 to 1. For the last non-zero transform coefficient 708(i.e., at r=2, c=2), as the absolute value of −1 (i.e., |−1|=1) is equalto k (i.e., 1), the process 600 sets the corresponding value 716 of thelevel-1 map 707 to 0. The last non-zero transform coefficient in thetransform block (e.g., the last non-zero transform coefficient 708) canbe referred to as the highest AC coefficient).

In an implementation, to generate a lower-level map, the process 600 canscan the preceding level map backwards starting at the last 1 value ofthe previous level map. For a level-k map, the preceding level map isthe level-(k−1) map corresponding to the preceding map level (k−1). Thatis, for k=2, the preceding level map is the level-1 map. For k=1, thepreceding level map is the level-0 map (i.e., the non-zero map). For thelevel-1 map 707, scanning of the non-zero map 706 starts at the lastnon-zero coefficient 710. For the level-2 map 709, scanning of thelevel-1 map 707 starts at the last non-zero coefficient 724. Ingenerating a level-k map, the process 600 need only process thetransform coefficients corresponding to 1 values in the level-(k−1). Theprocess 600 need not process the transform coefficients corresponding tonon 1 values as those values are already determined to either be equalto k−1 (i.e., the zero values of the level-(k−1) map) or are less thank−1 (i.e., the blank values of the level-(k−1) map).

In an implementation, the maximum map level T can be fixed. For example,the maximum map level T can be provided as a configuration to theprocess 600, the maximum map level T can be hard-coded in a program thatimplements the process 600, or the maximum map level T can be setstatistically or adaptively based on previously coded transform blocksor other blocks of the encoded video bitstream. Alternatively, themaximum map level Tis determined by the process 600. That is, theprocess 600 can test different values for the maximum map level T (i.e.,T=1, 2, 3, 4, . . . ) and determine which value provides the bestcompression performance. The value of the maximum map level T thatresults in the best compression can be encoded in the video bitstream,which a decoder, such as the decoder 500 of FIG. 5 can decode and use. Amaximum map level T of 2 or 3 has been determined to provide acceptablecompression as compared to other values for the maximum map level T.

At 606, the process 600 encodes a coefficient residual map. Eachresidual coefficient of the coefficient residual map corresponds to arespective (i.e., co-located) non-zero transform coefficient of thetransform block having an absolute value exceeding the maximum maplevel. The residual coefficient for a transform coefficient at location(r, c) of the transform block can be calculated using the formula (1):

residue[r][c]=absolute(coefficient[r][c])−T−1  (1)

FIG. 7 illustrates a coefficients residue map 734. In the example ofFIG. 7, the maximum map level Tis equal to two (2). As such, thecoefficients residue map 734 contains the residuals of the transformcoefficients of the transform block 704 the absolute values of which aregreater than 2. A residual coefficient is the extent to which theabsolute value of a transform coefficient exceeds the maximum map levelT. The absolute values of two values of the transform block 704 aregreater than the value of the maximum map level T (i.e., 2), namely thetransform coefficient 720 (i.e., |−7|=7>2) and transform coefficient 739(i.e., |4|=4>2). Respectively, the coefficients residue map 734 includesresidual 736 and residual 738. Using the formula (1), the residual 736is set to 5 (i.e., absolute(−7)−3=4) and the residual 738 is set to 1(i.e., absolute(4)−3=1).

The residual coefficients of the coefficients residue map 734 can beencoded in the encoded video bitstream using binary coding. Aprobability distribution that fits the statistics of the residualcoefficients of the coefficients residue map can be used. Theprobability distribution can be a geometric distribution, a Laplaciandistribution, a Pareto distribution, or any other distribution.

Encoding the residual coefficients in the encoded video bitstreamprovides several benefits, such as over video coding systems that encodethe transform coefficients. As each residual coefficient is smaller inmagnitude than its corresponding transform coefficient, less bits arerequired to encode the residual coefficient. Additionally, as there arefewer residual coefficients to encode (e.g., 2 in the coefficientresidual map 734 of FIG. 7) than non-zero transform coefficients (e.g.,7 in the transform block 704 of FIG. 7), additional compression canresult.

In an implementation of the process 600, a sign map can also be encoded.A sign map indicates which transform coefficients of the transform blockhave positive values and which transform coefficients have negativevalues. Transform coefficients that are zero need not be indicated inthe sign map. The sign map 732 of FIG. 7 illustrates an example of asign map for the transform block 704. In the sign map, negativetransform coefficients are indicated with a −1 and positive transformcoefficients are indicated with a 1. In some implementations, the signof a positive coefficient may be indicated with a 0 and the sign of anegative coefficient may be indicated with a 1.

In an implementation of the process 600, encoding a non-zero map, at602, can also include generating an end-of-block map for the transformblock and interleaving the non-zero map and the end-of-block map in theencoded video bitstream.

The end-of-block map indicates whether a non-zero transform coefficientof the transform block is the last non-zero coefficient with respect toa given scan direction. If a non-zero coefficient is not the lastnon-zero coefficient in the transform block, then it can be indicatedwith the binary value 0 (zero) in the end-of-block map. If, on the otherhand, a non-zero coefficient is the last non-zero coefficient in thetransform block, then it can be indicated with the binary value 1 (one)in the end-of-block map.

For example, as the transform coefficient 720 of the transform block 704is followed by another non-zero transform coefficient (e.g., thetransform coefficient −1 corresponding to scan location 2), thetransform coefficient 720 is not the last non-zero transformcoefficient, it is indicated with the end-of-block value 728 of zero. Onthe other hand, as the transform coefficient corresponding to the scanlocation 11 (i.e., the last non-zero transform coefficient 708) is thelast non-zero coefficient of the transform block 704, it is indicatedwith the end-of-block value 730 of 1 (one).

The process 600 can, by traversing the non-zero map and the end-of-blockmaps in a same scan direction, interleave values from the non-zero map706 and the end-of-block map 726 in the encoded bitstream. The process600 can use the zigzag forward scan direction 702 or any arbitrary scandirection. For each position (r, c), the value at that row and column ofthe non-zero map 706 (i.e., nz_map[r][c]) is coded first. If the valuenz_map[r][c] is 1, then the corresponding value from the end-of-blockmap 726 (i.e., eob_map[r][c]) is coded next to indicate whether theposition (r, c) of the transform block 704 contains the last nonzerotransform coefficient. The process 600 ends the coding of the non-zeromap (e.g., the non-zero map 706) when eob_map[r][c] equals to 1 or whenthe last position in the transform block (e.g., the scan position 15 ofthe zigzag forward scan direction 702) is reached. That is, whenencoding a value of 1 from the non-zero map 706, the value is followedby another syntax element (i.e., a value to be encoded in the encodedvideo bitstream) from a corresponding (i.e., co-located) end-of-blockmap 726 value to indicate whether the 1 value is the last 1 value of thenon-zero map 706.

In an implementation, encoding a non-zero map, at 602, can also includedetermining a coding context for a value (i.e., to-be-coded value) ofthe non-zero map. The coding context of a to-be-coded value at a currentposition (r, c) can be based on previously coded non-zero neighboringvalues of the to-be-coded value in the non-zero map. The coding contextcan also be based on the position of the to-be-coded value within thenon-zero map.

As mentioned above, the context information can be determined based onthe number of non-zero previously coded neighbors of the currentposition and can be calculated using the sum

non__zero__map_sum(r,c)=Σ_((r′,c′)∈nb(r,c)) nz_map(r′,c′)  (2)

In equation (2), non_zero_map_sum(r, c) is the number of non-zeropreviously coded neighbors of the to-be-coded value of the non-zeroblock at position (r, c), nb(r,c) is the set of previously codedneighbors of the to-be-coded value at location (r,c) of the non-zeromap, and nz_map(r′,c′) is the value at position (r′, c′) in the non-zeromap. Equation (1) is further explained with reference to FIG. 8.

FIG. 8 is a diagram of previously coded neighbors in a non-zero map 800according to an implementation of this disclosure. FIG. 8 includes ato-be-encoded value, current value 802, an unavailable context neighbor806 (i.e., a neighboring value for which context information is notavailable), and coded context neighbors, such as coded context neighbor808. Ten coded context neighbors are illustrated. Which values areincluded in the set of neighbors depends on the scan direction. Forexample, using the zigzag forward scan direction 702 of FIG. 7, the setof neighbors illustrated in FIG. 8 includes the coded context neighbors808 which includes neighbors that are above and to the left of thecurrent value 802. For the current value 802, non_zero_map_sum(2,2)=5.This value (i.e., 5) can be used as context information to determine aprobability model for coding the current value 802 of the non-zero map800.

As indicated above, the coding context can also be based on the positionof the to-be-coded value within the non-zero map or, equivalently, inthe transform block. The positions of the transform block can be groupedinto context groups. For example, four context groups can be set: afirst group corresponding to the DC coefficient (i.e., r=0 and c=0), asecond group corresponding to the top row except for the AC coefficient(i.e., r=0 and c>0), a third group corresponding to the left-most columnexcept for the AC coefficient (i.e., r>0 and c=0), and a fourth groupcorresponding to all other coefficients (i.e., r>0 and c>0). As such,the current value 802 corresponds to the fourth context group.

In an implementation, encoding a non-zero map, at 602, can also includedetermining a coding context for each value of the end-of-block map. Theprocess 600 can determine a context model for a to-be-encoded value ofthe end-of-block map based on the location of the to-be-encoded valuewith respect to the frequency information of the transform block. Thatis, the position of the transform coefficient in the transform block canbe used as the context for determining the context model for encoding acorresponding (i.e., co-located) to-be-encoded value of the end-of-blockmap. The transform block can be partitioned into areas such that eacharea corresponds to a context. The partitioning can be based on therationale that the likelihood is very low that the end-of-block is atthe DC location of the transform block but that the likelihood increasesfurther from the DC coefficient.

In some implementations, a lower-range level map can be a binary maphaving dimensions corresponding to the dimensions of the transform blockand, as indicated above, a map level k. A position of the lower-rangelevel map can be set to one (1) when a corresponding value in thepreceding level map (i.e., level map k−1 as described below) is one (1)and the corresponding transform coefficient is greater than the maplevel k of the lower-range level map. A position of the lower-rangelevel map can be set to a value of zero when a corresponding value inthe preceding level map has a value of one and the correspondingtransform coefficient is equal to the map level k of the lower-rangelevel map. A position of the lower-range level map can have no valuewhen a corresponding value in the preceding level map has a value ofzero.

In an implementation of the process 600, encoding a lower-range levelmap for a level, at 604, can also include determining, based on a scandirection of the lower-range level map, a level-map coding context for avalue of the lower-range level map. As indicated above, encoding a valueof a lower-range level map k amount to encoding a binary value, namelywhether the corresponding (i.e., co-located) transform coefficient ofthe transform block is equal k or is above k. The encoding of binaryvalues results in simple contexts. As such, multiple neighboring valuesof a value can be used as the context for determining a context modelfor the value.

As also indicated above, scanning of the lower-range level map canproceed in a backwards scan direction. As such, when encoding a value,neighboring values below and to the right of the to-be-encoded value(if, for example, the scan direction is the zigzag forward scandirection or 702 of FIG. 7) will have already been encoded. Therefore,first neighboring values (e.g., below and right neighboring values) inthe lower-range level map can be used as context. Additionally, secondneighboring values (e.g., top and left neighboring values) in theimmediately preceding level-(k−1) map can also be used as context. Thepreceding level map of a lower-range level-k map is the lower-rangelevel-(k−1) map, for k>2; and the preceding level map for the level-1map is the non-zero map.

As described above, the coding of the transform coefficients is amulti-pass process. In the first pass, the non-zero map 706, whichdescribes the locations of non-zero coefficients in the transform block,is coded following the forward scan direction. In subsequent passes, thevalues of the non-zero coefficients following the backward scandirection (i.e., from the position of the highest AC coefficient to theposition of the DC coefficient) are coded. Coding the non-zero map 706can be implemented using the steps:

-   -   1. Initialize i=0, where i denotes the scan position, and i=0        corresponds to the DC position (e.g., the transform coefficient        720).    -   2. Code a binary non-zero flag nz[i] indicating whether the        quantized transform coefficient at scan position i is zero. For        example, a zero value (nz[i]=0) can be coded when the quantized        transform coefficient is zero (i.e., the value in the non-zero        map 706 at scan position i is zero); otherwise (the value in the        non-zero map 706 at scan position i is 1), a one value (nz[i]=1)        is coded. In another example, a zero value (nz[i]=0) can be        coded when the quantized transform coefficient is not zero;        otherwise, a one value (nz[i]=1) is coded.    -   3. If nz[i] indicates that the transform coefficient at scan        position i is non-zero (e.g., nz[i]=1), then code a binary flag        indicating whether all the coefficients at scan positions higher        than i are all zero. That is, when a 1 value of the non-zero map        706 is coded, then a value at the same scan position in the        end-of-block map 726 is then coded.    -   4. Set i to the next scan position (i=i+1).    -   5. Repeat Steps 2-4 until EOB is met (i.e., until the        end-of-block value 730 is coded).    -   6. Set nz[j]=0 for all j>EOB. That is, set all transform        coefficients after the end-of-block value 730 to 0.

During the quantization process, such as described with respect to thequantization stage 406 of FIG. 4, a rate distortion optimizedquantization (RDOQ) process determines (e.g., calculates, selects,etc.), for transform coefficients of a transform block, respectivequantized transform coefficients according to a rate distortion cost ofeach of the quantized transform coefficients.

For example, in response to receiving a transform coefficient value x,the RDOQ may initially provide a quantized transform coefficient Q(x).The quantized transform coefficient Q(x) may be first obtained byminimizing the distortion (e.g., a loss in video quality). However, whenthe RDOQ considers the rate (e.g., a number of bits) of coding thequantized transform coefficient Q(x) in addition to the distortion, theRDOQ may obtain another quantized transform coefficient Q′(x) thatprovides a better overall rate distortion cost. This process cancontinue until an optimal quantized transform coefficient is obtainedfor the transform coefficient value x. As such, the quantizedcoefficient value of a transform coefficient may change during thecoding process of the transform coefficient and/or the transform blockthat includes the transform coefficient.

As described above, coding the non-zero map 706 uses a forward scandirection and coding the subsequent level maps uses a backward scan. Assuch, estimating the rate cost of changing a transform coefficient valuecan be difficult since the first pass and the second (or a subsequent)pass of coding use different scan directions: one forward and onebackward.

More specifically, in the first pass where the scan direction is forward(from the DC coefficient to the highest AC coefficient), a change to thequantized coefficient value at scan position i can impact the rate costof coding coefficients at scan positions j that follow the scan positioni (i.e., j>i); and in the second pass, where the scan direction isbackward (from the highest AC coefficient to the DC coefficient), achange to the quantized coefficient at scan position i can impact therate cost of coding coefficients at scan positions j′ that precede thescan position i (i.e., j′<i).

As such, to estimate the cost of coding a coefficient at scan positioni, information from transform coefficients at scan positions j>i andtransform coefficients at scan positions j′<i are required therebycreating a bi-directional dependency. This bi-directional dependency maysignificantly complicate the RDOQ process.

To avoid the bi-directional dependency, implementations according tothis disclosure can, instead of interleaving EOB indications (i.e.,end-of-block values of the end-of-block map 726) after non-zero valuesof the non-zero map 706, first code the EOB symbol and proceed toprocess the non-zero map 706 in a backward scan direction. As such,backward scan directions can be used for all passes of the coding of thetransform block using level maps. By using backward scan directions inall passes, only information from transform coefficients at scanpositions j following the scan position of a current transformcoefficient i (i.e., j>i) are required for estimating the rate cost ofcoding the coefficient at scan position i. As such, complexity isreduced, which in turns leads to more efficient implementation of theRDOQ. Accordingly, coding a transform block using level maps can beimplemented using the steps:

-   -   1. Code EOB.    -   2. Set nz[j]=0 for all j>EOB, and set nz[EOB]=1. Terminate the        process if EOB<1.    -   3. Initialize i=EOB−1.    -   4. Code nz[i] indicating whether the quantized transform        coefficient at scan position i is zero (nz[i]=0) or not        (nz[i]=1).    -   5. Seti=i−1.    -   6. Repeat Steps 3-5 until i=−1.

In the above steps, the EOB is as described with respect to FIGS. 6-7.That is the EOB indicates the location of the last non-zero coefficientof the transform block. However, other semantics for the EOB arepossible. For example, in an implementation, the EOB can indicate thelocation immediately after the last non-zero coefficient of thetransform block. As such, and referring to FIG. 7 for illustration, theEOB would indicate the scan position 12 (instead of the scan position 11as described with respect to FIGS. 6-7).

When the EOB indicates the position immediately after the last non-zerocoefficient, then the steps above can be given by the following:

-   -   1. Code EOB.    -   2. Set nz[j]=0 for all j EOB, and set nz[EOB−1]=1. Terminate the        process if EOB<1.    -   3. Initialize i=EOB−2.    -   4. Code nz [i] indicating whether the quantized transform        coefficient at scan position i is zero (nz[i]=0) or not        (nz[i]=1).    -   5. Seti=i−1.    -   6. Repeat Steps 3-5 until i=−1.

FIG. 9 is a flowchart diagram of a process 900 for coding a transformblock using level maps according to an implementation of thisdisclosure. The process 900 can be implemented by an encoder such as theencoder 400 of FIG. 4. When implemented by an encoder, coding meansencoding in an encoded bitstream, such as the compressed bitstream 420of FIG. 4. For example, the process 900 can be performed in whole or inpart by the entropy encoding stage 408 of the encoder 400. The process900 can be performed by a decoder such as the decoder 500 of FIG. 5.When implemented by a decoder, coding means decoding from an encodedbitstream, such as the compressed bitstream 420 of FIG. 5. For example,the process 900 can be performed in whole or in part by the entropydecoding stage 502 of the decoder 500 and the encoded video bitstreamcan be the compressed bitstream 420 of FIG. 5.

Implementations of the process 900 can be performed by storinginstructions in a memory such as the memory 204 of the receiving station106 to be executed by a processor such as CPU 202, for example.

The process 900 can be implemented using specialized hardware orfirmware. Some computing devices can have multiple memories, multipleprocessors, or both. The steps or operations of the process 900 can bedistributed using different processors, memories, or both. Forsimplicity of explanation, the process 900 is depicted and described asa series of steps or operations. However, the teachings in accordancewith this disclosure can occur in various orders and/or concurrently.Additionally, steps in accordance with this disclosure may occur withother steps not presented and described herein. Furthermore, not allillustrated steps or operations may be used to implement a method inaccordance with the disclosed subject matter.

At 902, the process 900 codes an end-of-block indicator of the transformblock. In an implementation, the scan position of the EOB can be coded.For example, and referring to FIG. 7, the scan position 11 correspondingto the last non-zero transform coefficient 708 can be coded. In anotherexample, the scan position 12, corresponding to the coefficientfollowing the last non-zero transform coefficient 708 in the forwardscan order, is coded. In an implementation, the end-of-block indicatorcan be coded using a context model.

At 904, the process 900 codes the non-zero map in the backward scandirection starting at the last non-zero coefficient of the transformblock. The non-zero map indicates which transform coefficients of atransform block have a zero value and which transform coefficients ofthe transform block have a non-zero value. The process 900 codes thenon-zero map that is similar to the non-zero map 706 of FIG. 7. Theprocess 900 codes a binary value indicating whether a quantizedtransform coefficient at a scan order is zero or non-zero. For example,for a scan position i, the process 900 can code a zero if the quantizedtransform coefficient at the scan position i is zero; otherwise a 1 iscoded.

At 906, the process 900 codes a respective lower-range level map havinga respective map level up to a maximum map level T. A lower-range levelmap having to a map level indicates the transform coefficients of thetransform block are equal, in absolute value, to the respective maplevel and which transform coefficients of the transform block are, inabsolute value, greater than the respective map level. When implementedby a decoder, the process 900 decodes values from the encoded videobitstream to reconstruct lower-range level-k maps encoded as describedwith respect to 604 of the process 600.

For example, to reconstruct a level-1 map, the process 900 starts fromthe highest non-zero transform coefficient traversing backwards todetermine which of transform coefficients are equal to 1 and which aregreater than 1. That is, using the reconstructed non-zero map of thenon-zero map 706 of FIG. 7, and starting at the last non-zerocoefficient 710 and traversing backwards to the value 740, the process900 reconstructs the level-1 map 707 of FIG. 7. For each 1 value of thereconstructed non-zero map, the process 900 decodes a value from theencoded video bitstream and reconstructs the level-1 map 707. The valuesdecoded by the process 900 are zero and one (1) values.

To reconstruct a level-2 map, the process 900 uses the same procedure asthat used to generate the level-1 map except that, instead of traversingthe reconstructed non-zero map, the process 900 uses the reconstructedlevel-1 map. The process 900 repeats all the steps until the maximum maplevel number of level maps are reconstructed.

In an implementation, the maximum map level T can be provided to theprocess 900 via a configuration. In another implementation, the maximummap level T can be signaled, by an encoder, in the encoded videobitstream. As such, the process 900 decodes the maximum map level T fromthe encoded video bitstream.

At 908, the process 900 codes a coefficient residual map. Each residualcoefficient of the coefficient residual map corresponds to a respectivetransform coefficient of the transform block having an absolute valuethat exceeds the maximum map level. When implemented by a decoder, theprocess 900 reconstructs, e.g., the coefficient residual map 734 of FIG.7. For each one (1) value of the level-T map, the process 900 decodes acorresponding residual value from the encoded bitstream to reconstructthe coefficient residual map 734 of FIG. 7.

In some implementations, the process 900 can include coding a sign map,at 910. The sign map can be a sign map such as described with respect tothe sign map 732 of FIG. 7. The sign map indicates which transformcoefficients of the transform block have positive values and whichtransform coefficients have negative values.

For a transform block of size N×N, in the worst case N×N−1 bins (binarysymbols) may need to be context coded to determine the EOB position. Forexample, when N=32, in the worst cost, a total of 1023 bins may becontext coded (i.e., coded using a context model) to determine the EOBposition.

Some implementations can use scan positions groups to reduce the numberof context-coded bins required to code the EOB position. As such, codingthe scan position corresponding to the end-of-block position can includecoding an index of a scan positions group that includes the scanposition and coding an offset within the scan positions group, theoffset corresponding to a position of the scan position within the scanpositions group.

In an implementation of level maps, the value EOB=0 can be reserved forindicate that all transform coefficients of the block are zero. That is,when EOB=0, then the block is an all-zero block.

In an example of such implementations, the scan positions can bepartitioned (e.g., grouped) into 11 scan positions groups: 1, 2, [3, 4],[5-8], [9-16], [17-32], [33-64], [65-128], [129-256], [257-512],[513-1024]. That is, the group with index 0 includes only the scanposition 1; the group with index 1 includes only the scan position 2;the group with index 4 includes the scan positions 9-16; and so on. Forexample, assuming that the scan position 50, corresponding to the EOB,is to be coded, then the index 6 of a scan positions group [33-64] thatincludes the scan position 50 is coded and the offset 17 (i.e.,50−33=17) within the scan positions group [33-64] is coded.

In an implementation, the index of the group that includes the codedscan position corresponding to the end-of-block is context-coded (i.e.,is coded using arithmetic coding using a context model) and the offsetwithin the scan positions group can be coded in by-pass mode. By-passmode, which may also be referred to as the literal mode, means that thevalue to be coded is not coded using a context model. The by-pass modecan be used, for example, when the offset values within a range areequally probable. To code the offset 17, five (5) bits are required. Assuch, in this example, the number of context coded bins for EOB is atmost 10 corresponding to the group indexes {0, 1, . . . , 10}.

In an implementation, the index of the group that includes the codedscan position corresponding to the end-of-block is context-coded (i.e.,coded using a context model) and at least some of the most significantbits of the offset within the scan positions group can also becontext-coded. That is, the offset value can be considered to includeprefix bits (i.e. most significant bits) and suffix bits (i.e., leastsignificant bits). The prefix bits can be context-coded and the suffixbits can be coded using by-pass mode. Any number of bits of the offsetvalue can be considered the most significant bits. For example, theoffset value 17 corresponds to the binary string 10001. If the first 2bits are considered most significant, then the bits 10 are context-codedand the bits 001 are by-pass coded (i.e., coded using by-pass mode). Ifthe first 3 bits are considered most significant, then the bits 100 arecontext-coded and the bits 01 are by-pass coded.

The scan positions can be grouped into scan position groups in anynumber of ways. In an implementation, and as illustrated by the abovegroup, each group can include a power of 2 number of scan positions. Thepower of 2 can be the index scan position groups minus 1 (i.e.,index−1). For example, the scan position groups at index 5 (i.e., thegroup [17-32]) includes 2⁵⁻¹ (=2⁴=16) scan positions. As such, to codean offset within a scan position groups having an index inx, only(inx−1) bits are required. For example, one (1) bit is required to codean offset in the group having index 2 (the group [3,4]), two (2) bitsare required to code an offset in the group having index 3 (the group[9-16]), and so on.

In an implementation, the number of scan positions in each scanpositions group can be limited to a maximum predetermined number (i.e.,a ceiling). For example, the group size can be limited to no greaterthan 16. As such, the above group can be modified as follows: 1, 2, [3,4], [5-8], [9-16], [17-32], [33-48], [49-64], . . . , [1009-1024]. Assuch, coding an offset requires no more than 4 bits. To code an EOBposition of 50 using the modified groups, the index 7, which correspondsto the scan positions group [49-64], can be coded using arithmeticcoding with context models. The offset 1 (=50-49) can be coded in bypassmode by using 4 bits, namely 0001.

In some implementations, the value EOB=0 is not reserved for indicatingthat all transform coefficients of the block are zero. In suchimplementations, the scan positions groups can start at 0 and end at1023, such as 0, 1, [2, 3], [4-7], [8-15], [16-31], [32-63], [64-127],[128-255], [256-511], [512-1023].

As described above, the values of the non-zero map 706 include binaryvalues. The binary values indicate whether a transform coefficient at agiven location of the transform block is zero or non-zero. As such, thevalues of the non-zero map can be considered non-zero flags. The binaryvalues enable the use of sophisticated spatial neighboring templates forcontext modeling. Such spatial neighboring templates can better capturestatistical characteristics of transform blocks, especially those withlarger transform block sizes. Accordingly, the coding of non-zero flags(and thus, the coding of transform coefficients) can be improved byfully utilizing the information of neighboring non-zero flags whendetermining a context for selecting a context model.

A template captures the coded history of the non-zero flags (i.e.,values of the non-zero map) that are coded before a current non-zeroflag. A template can define (e.g., specify, select, set, or define inany manner whatsoever), for a current scan position, the scan positionsof the non-zero map values that are to be used for determining thecontext for coding the current value. Equivalently, a template can bedefined in terms of the Cartesian coordinates, within the non-zero map,of the non-zero values to be used for determining the context.

FIGS. 10A-10B is a diagram of examples 1000 of templates for determininga coding context according to implementations of this disclosure. InFIGS. 10A-10B, values (i.e., circles representing values of a non-zeromap) shaded using the pattern 1004 are to-be-coded values; and thevalues shaded with the pattern 1002 are values for which contextinformation are available because these values are coded before ato-be-coded value 1032. In the examples of FIGS. 10A-10B, theto-be-coded value 1032 depicts the current value of the non-zero map tobe coded. The examples of FIGS. 10A-10B are non-limiting examples.Templates having other shapes and/or sizes are also possible.

In an example, the number of non-zero values corresponding to thetemplate positions can be used as the context for coding the currentvalue. For example, the values corresponding to the template positionscan be added and the sum can be used as the context. In some cases, acontext position 1002 may not be available, such as, for example, if thecontext position is outside the boundaries of the block. In an example,an unavailable value can be assumed to be zero (0). In another example,an unavailable value can be assumed to be one (1).

A codec can use multiple transform types. For example, a transform typecan be the transform type used by the transform stage 404 of FIG. 4 togenerate the transform block. For example, the transform type (i.e., aninverse transform type) can be the transform type to be used by thedequantization stage 504 of FIG. 5. Available transform types caninclude a one-dimensional Discrete Cosine Transform (1D DCT) or itsapproximation, one-dimensional Discrete Sine Transform DST (1D DST) orits approximation, a two-dimensional DCT (2D DCT) or its approximation,two-dimensional DST (2D DST) or its approximation, and an identitytransform. Other transform types can be available. In an example, aone-dimensional transform (1D DCT or 1D DST) can be applied in onedimension (e.g., row or column) and the identity transform applied inthe other dimension.

In the cases where a 1D transform (e.g., 1D DCT, 1D DST) is used (e.g.,1D DCT is applied to columns (or rows, respectively) of a transformblock), the quantized coefficients can be coded by using a row-by-row(i.e., raster) scanning order or a column-by-column scanning order. Inthe cases where 2D transforms (e.g., 2D DCT) are used, a differentscanning order may be used to code the quantized coefficients. Asindicated above, different templates can be used to derive contexts forcoding the non-zero flags of the non-zero map based on the types oftransforms used. As such, in an implementation, the template can beselected based on the transform type used to generate the transformblock. As indicated above, examples of a transform type include: 1D DCTapplied to rows (or columns) and an identity transform applied tocolumns (or rows); 1D DST applied to rows (or columns) and an identitytransform applied to columns (or rows); 1D DCT applied to rows (orcolumns) and 1D DST applied to columns (or rows); a 2D DCT; and a 2DDST. Other combinations of transforms can comprise a transform type.

As indicated above with respect to FIG. 9, the non-zero map can be codedin the backward scan direction starting at the last non-zero coefficient(i.e., starting at the highest AC transform coefficient) of thetransform block. As such, the coded history of a current value (i.e., acurrent non-zero flag) of the non-zero map includes values that are tothe right and below the current value in the two-dimensional non-zeromap, such as the non-zero map 706.

When a 1D vertical transform type is applied, the to-be-coded value 1032is more correlated with vertical neighbor values than with horizontalneighbor values. As such, a template 1010 can be used in the case a 1Dtransform (e.g., 1D DCT) is applied to columns. Assuming that theto-be-coded value 1032 is at position (x, y) of the non-zero map, thenthe template 1010 comprises the values at the seven positions (x+1, y),(x+2, y), (x+3, y), (x+4, y), (x, y+1), (x+1, y+1), and (x+1, y+2).

When a 1D horizontal transform type is applied, the to-be-coded value1032 is more correlated with horizontal neighbor values than withvertical neighbor values. As such, a template 1020 can be used in thecase a 1D transform (e.g., 1D DCT) is applied to rows. Assuming that theto-be-coded value 1032 is at position (x, y) of the non-zero map, thenthe template 1020 comprises the values at the seven positions (x+1, y),(x, y+1), (x+1, y+1), (x, y+2), (x+1, y+2), (x, y+3), and (x, y+4).

When a 2D transform type (e.g., 2D DCT, 2D DST) is applied, a template1030 can be used. Assuming that the to-be-coded value 1032 is atposition (x, y) of the non-zero map, then the template 1030 comprisesthe values at the seven positions (x+1, y), (x+2, y), (x, y+1), (x+1,y+1), (x+2, y+1), (x, y+2), and (x+1, y+2).

In some examples of templates, the non-zero value that is scannedimmediately before the to-be-coded value 1032 is not included in thetemplate. That is, if the to-be-coded value 1032 is at scan position i,then the non-zero value at scan position (i−1) is not included in thetemplate. Even though the non-zero map is coded in a backward scandirection, the scan order of the scan direction can depend on thetransform type. The scan order of the backward scan direction is theorder in which non-zero values of the non-zero map are visited from thehighest AC value to the DC value. In an example, a vertical scan ordercan be used when a 1D horizontal transform type is used. As such, thescan direction proceeds in column-wise order (e.g., from bottom to top).In an example, a horizontal scan order can be used when a 1D verticaltransform type is used. As such, the scan direction proceeds in row-wiseorder (e.g., from right to left).

Template 1040 is another example of a template that can be used when a1D-transform type is applied to columns. In the template 1040, thenon-zero value that is scanned immediately before the to-be-coded value1032 is not included in the template. Assuming that the to-be-codedvalue 1032 is at position (x, y) of the non-zero map, then the template1040 comprises the values at the seven positions (x+1, y), (x+2, y),(x+3, y), (x+4, y), (x+1, y+1), (x+1, y+1), and (x+1, y+2).

Template 1050 is another example of a template that can be used when a1D-transform type is applied to rows. In the template 1050, the non-zerovalue that is scanned immediately before the to-be-coded value 1032 isnot included in the template. Assuming that the to-be-coded value 1032is at position (x, y) of the non-zero map, then the template 1040comprises the values at the seven positions (x, y+1), (x+1, y+1), (x,y+2), (x+1, y+2), (x, y+3), (x+1, y+3), and (x, y+4).

Template 1060 is an example of a template that can be used when a 2Dtransform (e.g., 2D DCT, 2D DST) is used. Assuming that the to-be-codedvalue 1032 is at position (x, y) of the non-zero map, then the template1040 comprises the values at the seven positions (x+1, y), (x+2, y),(x+3, y), (x, y+1), (x+1, y+1), (x, y+2), and (x, y+3).

Each of templates 1010-1060 includes seven (7) positions. However, atemplate can include more or less positions and/or can have othershapes. For example, template 1070 is another example of a template thatcan be used when a 2D transform type is used. The template 1070 includeseight (8) positions. Assuming that the to-be-coded value 1032 is atposition (x, y) of the non-zero map, then the template 1040 comprisesthe values at the eight positions (x+1, y), (x+2, y), (x+3, y), (x,y+1), (x+1, y+1), (x, y+2), (x+1, y+2), and (x, y+3).

In other examples, a template can include five (5) positions. Forexample, a template 1088 of FIG. 10B, which includes the positions (x+1,y), (x, y+1), (x+2, y), (x, y+2), (x+1, y+1), can be used for2D-transform types. For example, templates 1080, 1082, 1083 can be usedfor a vertical 1D-transform type. The template 1080 includes thepositions (x+1, y), (x+2, y), (x+3, y), (x+4, y), and (x, y+1). Thetemplate 1082 includes the positions (x+1, y), (x+2, y), (x+3, y), (x+4,y), and (x+1, y+1). The template 1083 includes the positions (x, y+1),(x, y+2), (x, y+3), (x+1, y), (x+1, y+1). For example, templates 1084,1086, and 1087 can be used for a horizontal 1D-transform type. Thetemplate 1084 includes the positions (x+1, y), (x+2, y), (x+3, y), (x,y+1), (x+1, y+1). The template 1086 includes the positions (x, y+1), (x,y+2), (x, y+3), (x, y+4), and (x+1, y+1). The template 1087 includes thepositions (x, y+1), (x, y+2), (x, y+3), (x, y+4), and (x+1, y). In someimplementation, the positions (x+1, y) and (x, y+1) can be replaced bythe positions (x+1, y+2) and (x+2, y+1), respectively.

In some implementations, coding of a level-k map, where k>0, can alsouse different templates (e.g., templates as described above) dependingupon transform types. For example, as described above, one template maybe used for 2D-transform type, one template may be used for vertical1D-transform type, and another template may be used for horizontal1D-transform type.

In some implementations, the contexts used to code the non-zero flagscan depend upon the locations (i.e., the scan positions or the blockpositions) of the non-zero flags. As such, in some implementations, thetransform-type-dependent templates, described above, can be combinedwith the locations of the non-zero flags to determine a context. Toavoid using too many contexts, which may lead to the so-called contextdilution problem, the locations can be classified into regions. Forexample, the classification may be dependent upon the transform type.

FIG. 16 is a diagram of examples 1600 of regions for determining acontext according to implementations of this disclosure. FIG. 16includes a vertical transform block 1602 (i.e., a transform block ofclass TX_CLASS_VERT), a horizontal transform block 1604 (i.e., atransform block of class TX_CLASS_HORIZ), and a 2D transform block 1606(i.e., a transform block of class TX_CLASS_2D). A transform classcorresponds to a transform type and a direction. The class TX_CLASS_VERTis referred to as a vertical transform class. The class TX_CLASS_HORIZis referred to as a horizontal transform class. The class TX_CLASS_2D isreferred to as a two-dimensional transform class.

The vertical transform block 1602 is a transform block generated using a1D vertical transform type as described above. As such, theTX_CLASS_VERT class includes the 1D transform types (e.g. DCT, DST,ADST, or their approximations) applied to columns (i.e., in the verticaldirection). The horizontal transform block 1604 is a transform blockgenerated using a 1D horizontal transform type as described above. Assuch, the TX_CLASS_HORIZ class includes the 1D transform types (e.g.DCT, DST, ADST, or their approximations) applied to rows (i.e., in thehorizontal direction). The 2D transform block 1606 is a transform blockgenerated using a 2D transform type as described above. As such, theTX_CLASS_2D class includes any remaining transform types applied to bothrows and columns.

A transform block of class TX_CLASS_VERT can be partitioned into R_(V)(>0) number of regions such that each region includes one or more rows.A transform block of class TX_CLASS_HORIZ can be partitioned into R_(H)(>0) number of regions such that each region includes one or morecolumns. A transform block of class TX_CLASS_2 D can be partitioned intoR_(2D) (>0) number of regions where each region includes one or moreanti-diagonal lines.

A transform block can be partitioned into regions in any number of ways.In an example, R_(V)=3, R_(H)=3, and R_(2D)=4 and the regionclassification is as follows:

For a transform block of class TX_CLASS_HORIZ, the first region (i.e.,region 1616) consists of the left most column (col=0), the second region(i.e., region 1618) consists of the second leftmost column (col=1), andthe third region (i.e., region 1620) consists of the remaining columns.

For a transform block of class TX_CLASS_VERT, the first region (i.e.,region 1610) consists of the top most row (row=0), the second region(i.e., region 1612) consists of the second top-most row (row=1), and thethird region (i.e., region 1614) consists of the remaining rows.

For a transform block of class TX_CLASS_2D, the first region (i.e.,region 1622) consists of the first anti-diagonal line (row+col=0), thesecond region (i.e., region 1624) consists of the second anti-diagonalline (row+col=1), the third region (i.e., region 1626) consists of thethird and the fourth anti-diagonal lines (row+col=2 or 3), and thefourth region (not shown) consists of the remaining anti-diagonal lines.

A region and a transform class (e.g. TX_CLASS_VERT, TX_CLASS_HORIZ,TX_CLASS_2D) combination can correspond to a set of contexts. In animplementation where a context may be retrieved using an offset(corresponding to the context) into an available list (e.g., table) ofcontexts, each set can be distinguished (e.g., identified) by the set'soffset. In some implementations, some of the transform classes can mapto the same offset. Mapping transform classes to the same offset meansthat the transform classes that are mapped to the same offset sharecontexts.

To derive a context for coding a transform coefficient at location (x,y) of the transform block, where each of the transform classes maps to adistinct offset (i.e., the transform classes do not share offsets), thecontext (i.e., ctx) can be derived as follows:

If the transform class = TX_CLASS_2D then  ctx = 0 if x =0 and y = 0  ((counts +1)>>1) + 1 if x+y < 2   ((counts +1)>>1) + 6 if x+y < 4  ((counts +1)>>1) + 11 otherwise If the transform class = TX_CLASS_VERTthen   ctx = ((counts +1)>>1) + 16 if y = 0    ((counts +1)>>1) + 16 + 5if y < 2    ((counts +1)>>1) + 16 + 10 otherwise If the transform class= TX_CLASS_HORIZ then   ctx = ((counts +1) >>1) + 31 if x = 0   ((counts +1)>>1) + 31 + 5 if x < 2    ((counts +1)>>1) + 31 + 10otherwise

In the above example, the offset for TX_CLASS_2D is zero (0), the offsetfor TX_CLASS_VERT is 16, and the offset for TX_CLASS_HORIZ is 31. In theexample, for a transform block of class TX_CLASS_2D, the first region(i.e., the DC coefficient only) has one context and each remainingregion has five (5) contexts. For a transform block of classTX_CLASS_VERT or TX_CLASS_HORIZ, each region has five (5) contexts.Further in the example above, counts (e.g., sums) are computed by usinga template of size 7 and that depends on the transform type class asdescribed above with respect to FIG. 10A. As such, (counts+1)>>1 is anumber between 0 and 4 (“>>1” right-shifts (counts+1) by 1 bit).

In the FIGS. 6-10, the coding of transform blocks (e.g., the transformcoefficients of the transform blocks) using level maps is described.However, other codecs can code the transform coefficients using acoefficient token tree and/or using an alphabet of coefficient tokensthat may be organized into a coefficient token tree.

In an example, to derive a context for coding a transform coefficient atlocation (x, y) of the transform block, where the TX_CLASS_VERT andTX_CLASS_HORIZ map to the same offset, the context (i.e., ctx) can bederived as follows:

If the transform class = TX_CLASS_2D then  ctx = 0 if x =0 and y = 0  ((counts +1)>>1) + 1 if x+y < 2   ((counts +1)>>1) + 6 if x+y < 4  ((counts +1)>>1) + 11 otherwise If the transform class is one of(TX_CLASS_VERT OR TX_CLASS_HORIZ) then  ctx = ((counts +1)>>1) + 16 if y= 0   ((counts +1)>>1) + 16 + 5 if y < 2   ((counts +1)>>1) + 16 + 10otherwise

Mapping some of the transform classes to a same offset can reduce thenumber of contexts. In at least some situations (e.g., depending on thecharacteristics of a video sequence being coded), mapping transformclasses (e.g., the transform classes TX_CLASS_VERT and theTX_CLASS_HORIZ) to a same offset can also result in an improved codingperformance. In general, intermingling (e.g., mixing) statistics maynegatively impact compression performance when the statistics aredifferent. However, since contexts given by the classes TX_CLASS_VERTand TX_CLASS_HORIZ can be similar in statistics, combining the contextsof these transform classes can show positive impact on compressionperformance by reducing the effect of the so-called context-dilutionproblem.

As described above with respect to FIG. 7, the level maps are codedsequentially. That is, the non-zero map 706 is coded, then the level-1map is coded, then the level-2 map is coded, and then the coefficientresidual map 734 is coded. However, in some implementations, a differentcoding structure can be used.

As described above with respect to FIGS. 10A-10B, coding of a level-kmap, where k>0, can also use different templates (e.g., templates asdescribed above) depending upon transform types. That is, a template, asdescribed above can be used to determine a context for coding whether acoefficient at (x, y) is greater than 1 (e.g., using a correspondingvalue of a level-1 map, such as the level-1 map 707 of FIG. 7) or isgreater than 2 (e.g., using a corresponding value of a level-2 map, suchas the level-2 map 709 of FIG. 7).

As such, each coefficient can be coded up to whether the coefficient isgreater than the maximum map level. In the example of FIG. 7, themaximum map level is 2. As such, each coefficient can be coded up towhether the coefficient is greater than 2 (using corresponding values oflevel maps) before proceeding to coding of a next coefficient. In animplementation, a coefficient value that is greater than 2 (i.e., acoefficient value that is greater than the maximum map level) can berepresented by the value 3 (i.e., the maximum map level+1). As such,coding a coefficient “up to whether the coefficient is greater thanmaximum map level (e.g., 2)” can mean coding a value 0, 1, 2, . . . ,(maximum map level+1) (e.g. 3) corresponding, respectively and in thecase what the maximum map level is 2, to a coefficient having a valueequal to 0, equal to 1, equal to 2, and greater than 2.

FIG. 17 is a flowchart diagram of a process 1700 for decoding atransform block using level maps according to an implementation of thisdisclosure. Unlike the process 900 which codes the level mapssequentially (i.e., each map is coded before proceeding to coding thenext map), the process 1700 codes, for each non-zero coefficient, usinga template, and in a case where the maximum map level is 2 (i.e., T=2),whether the coefficient is 0, 1, 2, or greater than 2 (represented bythe value 3). That is, the process 1700 codes a coefficient beforeproceeding to the next coefficient in the scan order. The process 1700can include blocks similar to those of the process 900. Descriptions ofthe similar blocks (e.g., 902, 908, and 910) are omitted. Someimplementations of the process 1700 can include the block 910 before theblock 908.

The process 1700 can be implemented by an encoder such as the encoder400 of FIG. 4. When implemented by an encoder, coding means encoding inan encoded bitstream, such as the compressed bitstream 420 of FIG. 4.For example, the process 1700 can be performed in whole or in part bythe entropy encoding stage 408 of the encoder 400. The process 1700 canbe performed by a decoder such as the decoder 500 of FIG. 5. Whenimplemented by a decoder, coding means decoding from an encodedbitstream, such as the compressed bitstream 420 of FIG. 5. For example,the process 1700 can be performed in whole or in part by the entropydecoding stage 502 of the decoder 500 and the encoded video bitstreamcan be the compressed bitstream 420 of FIG. 5.

Implementations of the process 1700 can be performed by storinginstructions in a memory such as the memory 204 of the receiving station106 to be executed by a processor such as CPU 202, for example.

The process 1700 can be implemented using specialized hardware orfirmware. Some computing devices can have multiple memories, multipleprocessors, or both. The steps or operations of the process 1700 can bedistributed using different processors, memories, or both. Forsimplicity of explanation, the process 1700 is depicted and described asa series of steps or operations. However, the teachings in accordancewith this disclosure can occur in various orders and/or concurrently.Additionally, steps in accordance with this disclosure may occur withother steps not presented and described herein. Furthermore, not allillustrated steps or operations may be used to implement a method inaccordance with the disclosed subject matter.

At 1702, the process 1700 determines whether there are more non-zerocoefficients to code. If so, the process 1700 proceeds to 1704 to code acurrent quantized transform coefficient at (x, y); otherwise, theprocess 1700 proceeds to 908. At 1704, the process 1700 selects atemplate for coding a current quantized transform coefficient. As usedin this disclosure, “select” means to identify, construct, determine,specify, generate, or other select in any manner whatsoever. Thetemplate can be a template as described with respect to FIGS. 10A-10B.In an example, the same template is used for coding all the coefficientsof the transform block. As such, the template can be selected once forthe process 1700 and be performed before the block 1702.

At 1706, the process 1700 determines a context using the template. Theprocess 1700 can determine the context using the template in any numberof ways. Each template position corresponds to a value (e.g., 0, 1, . .. , T+1). Combinations of the values can be used to determine thecontext. For example, a sum of the values can be used. For example, aweighted sum can be used to determine the context. The weight assignedto a position can be set based on the distance to the “origin” (i.e.,the location (x, y) of the current transform coefficient for which thecontext is determined). Examples of distance include a scan positiondistance (e.g., a difference between the scan position of the currentcoefficient and a position of the template) or a Cartesian distance.However, other ways of setting the weight can be available. In yetanother example, a non-linear function can be used. For examples, themaximum or minimum value in the template can be used for determining thecontext. In yet another example, the context can be determined using acombination of the sum and the maximum values. Other methods and/orvalues, or combinations of methods and/or values, can be used fordetermining the context from the template.

Using the sum (i.e., addition) of the values at the positions of thetemplate to determine a context is now given. It should be understoodthat the following can be used with any method for determining thecontext using the template.

The process 1700 can add up (sums) the values corresponding to thepositions of the template. When using a template for deriving a contextfor coding a coefficient, each of the positions of the template can haveone of the values 0, 1, 2, or 3 (i.e., when T=2). As such, if thetemplate includes N positions, then the maximum sum can be 3*N. Forexample, if a template that includes 5 positions is selected at 1704,then the maximum sum can be 15 (=3*5); if a template that includes 7positions is selected, then the maximum sum can be 21 (=3*7).

In an implementation, where level maps as described with respect to FIG.7 are used, to determine a value for a position of the template, thevalues, at the same positions in the non-zero maps and the level-k mapscan be added or counted. For example, assuming that the position of thelast non-zero transform coefficient 708 is a position of the template,then the value of the template at that position can be determined to bethe sum of the values at 712 (i.e., 1) and 716 (i.e., 0) of the non-zeromap 706 and level-1 map 707. As such, the value is 1. As another,assuming that the position of the transform coefficient 739 is aposition of the template, then the value of the template at thatposition can be determined to be the sum of the values at thecorresponding locations of in the non-zero map 706, the level-1 map 707,and the level-2 map 709. As such, the value is 3. As such, the contextindex can be determined using a sum of the values corresponding topositions of the template where each value of the template is determinedby summing respective values of at least some of the level maps.

In another implementation, the level maps, including the zero map and asdescribed with respect to FIG. 7 are not generated. Instead, a singlemap level can be used to indicate, whether a transform coefficient isone of 0, 1, . . . , T+1. As such, given a scan position i, level[i]={0,1, . . . T+1}. The single map can include values for all transformcoefficients of the transform block. Alternatively, the single map caninclude values for coefficients up to the end-of-block coefficient. Thatis, the single map level can include values for each transformcoefficient up to and including the last non-zero coefficient of thetransform block.

As such, the sum for determining the context can be generated by addingthe respective values of the single map level. For example, assumingthat the template includes 5 positions corresponding to the scanpositions l₁, l₂, l₃, l₄, and l₅, then the sum can be determined assum=level[l₁]+level[l₂]+level[l₃]+level[l₄]+level[l₅].

Using the sum, the process 1700 can determine a context index (i.e.,ctx). The context index can be determined using an operation that issimilar to the operation ((counts+1)>>1) as described above. However,instead of using “count,” a “sum” is used. As such, the process 1700uses ((sum+1)>>1) for determining the context index.

The context index ctx may be out of range. For example, assuming thatthe sum is 15, the transform class is TX_CLASS_2D, and that (x, y) is(1, 2), then the context index is ((sum+1)>>1)+6=((15+1)>>1)+6=14.However, the number of available contexts for the TX_CLASS_2D, using theabove example, is 11. As such, the context index is out of range.Equivalently, a sum that results in a context index that is out of rangecan itself be considered out of range. If the context index is out ofthe range, then, the process 1700 can set the context index to apredetermined number. As such, the process 1700 can determine thecontext index using a formula such as min(((sum+1)>>1), predeterminednumber). As such, the value ((sum+1)>>1) is upper-bounded by thepredetermined number. In an example, the predetermined number can be 4.In an example, the predetermined number can depend on the transformclass type. The predetermined number can be selected in any other ways.

The context index ctx can be used to select a context for coding thecurrent transform coefficient. At 1708, the process 1700 codes thecoefficient using the context.

An implementation of the process 1700 that uses the single map level forcoding transform coefficients of the transform block can be summarizedusing the following procedure:

1. for (i=eob-1; i>=0; i--) { 2.  if (i < eob-1) code level [i]>0; 3. if (level [i] > 0) { 4.   for (j=0; j<T; j++) { 5.    code level [i] >j+1 6.    if (level [i] == j+1) 7.     break; 8.   } 9.  } 10. } 11. for(i==0; i < eob; i++) { 12.  if level [i] != 0 13.   code sign [i] 14. }15. for (i=eob-1; i >= 0; i--) 16.  if level [i] > T 17.   code level[i]-T-1

The steps 1-10 are repeated for each transform coefficient up to thelast non-zero coefficient of the transform block. For a transformcoefficient at scan position i, the steps 2-9 code up to whether atransform coefficient of the transform block is greater than a maximummap level of the level maps. For example, assuming that the maximum maplevel T=2 and i<eob-1, if level[i]=3, then the steps 2-9 code the bits111; if level[i]=0, then the steps 2-9 code the bit 0; and iflevel[i]=2, then the steps 2-9 code the bits 110. The steps 11-14 codethe sign bits (e.g., the values of the sign map 732 of FIG. 7) of thenon-zero transform coefficients up to the last non-zero coefficient. Thesteps 15-17 code, for each non-zero coefficient that is greater than themaximum level map T (i.e., level[i]>T), a residual for the transformcoefficient. The values of the residuals can be as described withrespect to the coefficient residual map 734.

Using the coding structure described in FIG. 17 for coding a transformcoefficient (i.e., a quantized transform coefficient), as compared tothe coding structure described with respect to FIG. 9, better throughputcan be obtained. Better throughput can mean that a transform block canbe decoded faster using the coding structure of the process 1700 thanthat of the process 900.

FIG. 11 is a diagram of a coefficient token tree 1100 that can be usedto entropy code transform blocks according to implementations of thisdisclosure. The coefficient token tree 1100 is referred to as a binarytree because, at each node of the tree, one of two branches must betaken (i.e., traversed). The coefficient token tree 1100 (which may alsobe referred to as a binary token tree) specifies the scope (e.g.,magnitude) of the value of a transform coefficient to be coded, withforward-adaptive probabilities for each branch in this token tree. Thetoken base value is subtracted from the value to be coded to form aresidual then the block is coded with fixed probabilities. A similarscheme with minor variations including backward-adaptivity is alsopossible.

Using the coefficient token tree 1100, a string of binary digits isgenerated for a quantized coefficient of the quantized transform block(such as the transform block 704 of FIG. 7). Each of the binary digitsis coded. Herein, “coding a bit” can mean the outputting or generatingof a bit in the codeword representing a transform coefficient beingencoded. Similarly, “decoding a bit” can mean the reading (such as froman encoded bitstream) of a bit of the codeword corresponding to aquantized transform coefficient being decoded such that the bitcorresponds to a branch being traversed in the coefficient token tree.The bits are entropy coded using a context.

In an example, the quantized coefficients in an N×N block (e.g., thetransform block 704) are organized into a 1D (one-dimensional) array(herein, an array u) following a prescribed scan direction (e.g., thescan order 702 of FIG. 7). N can be 4, 8, 16, 32, or any other value.The quantized coefficient at the it h position of the 1D array can bereferred as u[i], where i=0, . . . , N*N−1.

In an implementation, the end-of-block (EOB) can indicate the positionof the last non-zero coefficient. However, in other implementations, andin the subsequent description of FIG. 11, unless otherwise specified,the EOB denotes the starting position of the last run of zeroes in u[i],. . . ,u[N*N−1].

In the case where when u[N*N−1] is not zero, the EOB can be set to thevalue N*N. That is, if the last coefficient of the 1D array u is notzero, then EOB can be set to the value N*N. The values at each of theu[i]s are quantized transform coefficients. The quantized transformcoefficients of the 1D array u may also be referred herein simply as“coefficients” or “transform coefficients.” The coefficient at positioni=0 corresponds to the DC coefficient. In this example, the eob is equalto 12 because there are no non-zero coefficients after the zerocoefficient at position 12 of the 1D array u.

To encode and decode the coefficients u[i], u[N*N−1], for i=0 to N*N−1,a token t[i] is generated at each position i<=eob. The token t[i], fori<eob, can be indicative of the size and/or size range of thecorresponding quantized transform coefficient at u[i]. The token for thequantized transform coefficient at EOB can be an EOB_TOKEN, which is atoken that indicates that the 1D array u contains no non-zerocoefficients following the eob position (inclusive). That is,t[eob]=EOB_TOKEN indicates the EOB position of the current block. TableI provides a listing of an example of token values, excluding theEOB_TOKEN, and their corresponding names according to an implementationof this disclosure.

TABLE I Token Name of Token 0 ZERO_TOKEN 1 ONE_TOKEN 2 TWO_TOKEN 3THREE_TOKEN 4 FOUR_TOKEN 5 DCT_VAL_CAT1 (5, 6) 6 DCT_VAL_CAT2 (7-10) 7DCT_VAL_CAT3 (11-18) 8 DCT_VAL_CAT4 (19-34) 9 DCT_VAL_CAT5 (35-66) 10DCT_VAL_CAT6 (67-2048)

In an example, quantized coefficient values are taken to be signed12-bit integers. To represent a quantized coefficient value, the rangeof 12-bit signed values can be divided into 11 tokens (the tokens 0-10in Table I) plus the end of block token (EOB_TOKEN). To generate a tokento represent a quantized coefficient value, the coefficient token tree1100 can be traversed. The result (i.e., the bit string) of traversingthe tree can then be encoded into a bitstream (such as the bitstream 420of FIG. 4) by an encoder as described with respect to the entropyencoding stage 408 of FIG. 4.

The coefficient token tree 1100 includes the tokens EOB_TOKEN (token1102), ZERO_TOKEN (token 1104), ONE_TOKEN (token 1106), TWO_TOKEN (token1108), THREE_TOKEN (token 1110), FOUR_TOKEN (token 1112), CAT1 (token1114 that is DCT_VAL_CAT1 in Table I), CAT2 (token 1116 that isDCT_VAL_CAT2 in Table I), CAT3 (token 1118 that is DCT_VAL_CAT3 in TableI), CAT4 (token 1120 that is DCT_VAL_CAT4 in Table I), CAT5 (token 1122that is DCT_VAL_CAT5 in Table I) and CAT6 (token 1124 that isDCT_VAL_CAT6 in Table I). As can be seen, the coefficient token treemaps a single quantized coefficient value into a single token, such asone of the tokens 1104, 1106, 1108, 1110 and 1112. Other tokens, such asthe tokens 1114, 1116, 1118, 1120, 1122 and 1124, represent ranges ofquantized coefficient values. For example, a quantized transformcoefficient with a value of 37 can be represented by the tokenDCT_VAL_CAT5—the token 1122 in FIG. 11.

The base value for a token is defined as the smallest number in itsrange. For example, the base value for the token 1120 is 19. Entropycoding identifies a token for each quantized coefficient and, if thetoken represents a range, can form a residual by subtracting the basevalue from the quantized coefficient. For example, a quantized transformcoefficient with a value of 20 can be represented by including the token1120 and a residual value of 1 (i.e., 20 minus 19) in the encoded videobitstream to permit a decoder to reconstruct the original quantizedtransform coefficient. The end of block token (i.e., the token 1102)signals that no further non-zero quantized coefficients remain in thetransformed block data.

In another example of transform coefficient coding, the tokens availablefor coding transform coefficients can be split into groups of tokens.The available tokens can be organized as described with respect to thecoefficient token tree 700. In an example, the tokens are split into twosets of tokens: a set of head tokens and a set of tail tokens. A tokenof the set of head tokens is referred to herein as a head token. A tokenof the set of tail tokens is referred to herein as a tail token. Thesplit into groups of tokens may be logical. That is, for example, atoken can be considered to be part of a group even though there may notbe stored data indicating that the token is in the group.

When coding the DC transform coefficient, the set of head tokensincludes the tokens BLOCK_Z_TOKEN, ZERO_TOKEN, ONE_NEOB, ONE_EOB,TWO_PLUS_NEOB, and TWO_PLUS_EOB. That is, when coding the DCcoefficient, the set of head tokens can include six (6) tokens. The DCcoefficient corresponds to the first scan position in a forward scandirection. The BLOCK_Z_TOKEN indicates that there are no non-zerocoefficients in the transform block. The BLOCK_Z_TOKEN can have a valueof 255.

When coding a transform coefficient other than the DC transformcoefficient, the set of head tokens includes the tokens: ZERO_TOKEN,ONE_NEOB, ONE_EOB, TWO_NEOB, and TWO_EOB. That is, when coding acoefficient other than the DC coefficient, the set of head tokensincludes five (5) tokens. A coefficient other the DC coefficient is acoefficient that does not correspond to the first scan position in theforward scan direction.

The token ZERO_TOKEN (which, in an example, can have a value of 0) canindicate that the transform coefficient coded with the ZERO_TOKEN has avalue of 0. The token ONE_EOB (which, in an example, can have a valueof 1) can indicate that the current transform coefficient has a value of1 and is followed by the EOB. That is, the current transform coefficientis the last non-zero coefficient of the transform block. The tokenONE_NEOB (which, in an example, can have a value of 2) can indicate thatthe current transform coefficient has a value of one and is not the lastnon-zero transform coefficient of the transform block.

The token TWO_PLUS_EOB (which, in an example, can have a value of 3) canindicate that the current transform coefficient has a value that isgreater than two (2) and is followed by the EOB. That is, the currenttransform coefficient is the last non-zero coefficient of the transformblock. The token TWO_PLUS_NEOB (which, in an example, can have a valueof 4) can indicate that the current transform coefficient has a valuethat is greater than two (2) and is not the last non-zero transformcoefficient of the transform block. If either the TWO_PLUS_EOB or theTWO_PLUS_NEOB token is coded, then a token from the tail set of tokensis also coded.

The set of tail tokens includes the tokens: TWO_TOKEN, THREE_TOKEN,FOUR_TOKEN, DCT_VAL_CAT1, DCT_VAL_CAT2, DCT_VAL_CAT3, DCT_VAL_CAT4,DCT_VAL_CAT5 and DCT_VAL_CAT6. The set of tail tokens includes nine (9)tokens. A token from the set of tail tokens is used only if a TWO_EOB orTWO_NEOB in the set of head tokens is coded. As mentioned elsewhere,coded means encoded by an encoder or decoded by a decoder.

A codec can use the same information to derive a context for coding atoken, whether the token is a head token or tail token. In an example,the information used to determine the context includes: a transformsize, a plane type, a reference type, a band position, and a coefficientcontext.

The transform size is the smallest square transform size that covers thetransform used to generate the transform block being coded. In anexample, the transform size can be one of the values {TX_4×4, TX_8X8,TX_16X16, TX_32X32} corresponding respectively to square transform sizes4×4, 8×8, 16×16, and 32×32. For example, if a transform of size 8×16 isused to generate the transform block, then the transform size fordetermining the coding context is the value TX_16×16. As anotherexample, if a transform of size 8×4 is used to generate the transformblock, then the transform size for determining the coding context is thevalue TX_8X8.

The plane type indicates whether the current transform block is aluminance block or a chrominance block. As such, the plane type can havethe values {PLANE_TYPE_Y, PLANE_TYPE_UV} where PLANE_TYPE_Y correspondsto a transform block of a luminance block and PLANE_TYPE_UV correspondsto transform block of a chrominance block (a U or V chrominance block).

The reference type can have one of the values {0, 1}. The reference typeindicates whether the source block, from which the transform blockresulted, was intra-predicted or not. If the block was intra-predicted,then the reference type can be zero (0); otherwise reference type is one(1).

Band position can have one of the values {0, 1, 2, 3, 4, 5}. The scanposition of a current coefficient is mapped to one of the bands {0, 1,2, 3, 4, 5}. The band positions constitute a mapping from scan positionsto a band position. For example, scan positions 0-4 may be mapped toband position 0, scan positions 5-9 may be mapped to band position 1,scan positions 10-16 may be mapped to band position 2, and so on. Assuch, if the coefficient at scan position 12 is being encoded, then theband position is 2. Other mappings are possible.

The coefficient context can have one of the values {0, 1, 2, 3, 4, 5}.In an example, the combined sum of the left and above neighbor transformcoefficients of the current coefficient can be mapped to one of thevalues {0, 1, 2, 3, 4, 5}.

As such, the total number of possible contexts is 576 (=4 transformsizes*2 reference types*2 reference types*6 band positions*6 coefficientcontexts). Each context provides a probability distribution for codingthe coefficient tokens. For example, a probability distribution forcoding one of the nine (9) tail tokens includes nine (9) probabilities.However, as the sum of the probabilities in a probability distributionis equal to 1, the context need provide only eight (8) probabilitieswhere the ninth can be derived. As such, given an alphabet of N (e.g.,9) symbols (e.g., tokens), N−1 (e.g., 9−1=8) total number of freedoms inthe probabilities are required. That is, for example, N−1 probabilityvalues need be stored and retrieved.

For the above described set of head tokens and set of tail tokens, thetotal number of freedoms is given by: the number of freedoms for thehead tokens when not coding the DC coefficient+the number of freedomsfor the head tokens when coding the DC coefficient+the number offreedoms for the tail tokens. The total number of freedoms is 7008(2304+96+4608):

-   -   1. The number of freedoms for the head tokens when not coding        the DC coefficient is =576*4=2304. Four (4) is the number of        tokens in the set of head tokens minus 1 (i.e., 5-1).    -   2. The number of freedoms for the head tokens when coding the DC        coefficient is =4×2×2×1×6=96. The 96 corresponding to 4        transform sizes multiplied by 2 plane types multiplied by 2        reference types multiplied by 1 band position multiplied by 6        coefficient contexts. When coding the DC coefficient, the number        of possible band positions is one (1) because the position of        the DC coefficient is known/fixed in the transform block.    -   3. The number of freedoms for the tail tokens is =576*8=4608.        Eight (8) is the number of tokens in the set of tail tokens        minus 1 (i.e., 9-1).

If each probability is stored by using N bits, where N is an integervalue, then a total of 7008*N bits are needed to store the probabilitiesneeded for coefficient coding. In the case where N is 8, 54K bits ofmemory are required; in the case where N is 16, 108K bits are required.

Implementations according to this disclosure can reduce the amount ofstorage required to store probability distributions for coding transformcoefficients by using different contexts for the coding head tokens thanthe contexts for tail tokens.

For example, whereas coding head tokens can use the context informationdescribed above, fewer band positions can be used for determining acontext for tail tokens. For example, instead of using six (6) bandpositions as described above, three (3) band positions, {0, 1, 2}, canbe used for tail tokens. As mentioned above, whereas a head token can becoded without coding a tail token, a tail token is coded only if aTWO_NEOB or a TWO_EOB head token is coded. As such, if a band positionof the corresponding head token is greater than 2, then the bandposition of the tail token can be taken to be the band value 2. Theprobability distributions of tail tokens may not be sensitive to bandpositions that are larger than or equal to two given coefficientcontexts.

In another example, whereas coding head tokens can use the contextinformation and values described above, fewer transform types can beused for determining a context for tail tokens as the probabilitydistributions of tail tokens do not seem to be sensitive to largetransform types given coefficient contexts and band positions. Forexample, instead of using four (4) transform types as described above,three (3) transform types, for example {TX_4X4, TX_8X8, TX16X16_Above},can be used for tail tokens. If the transform type of the correspondinghead token is one of TX_16X16, and TX_32X32, then the valueTX_16X16_Above can be used for the tail token.

Using three band transform types for tail tokens, the number of contextsused to code tail tokens is 288 (=4*2*2*3*6=4 transform sizes*2 planetypes*2 reference types*3 band positions*6 coefficient contexts)resulting in a 50% reduction in contexts for coding tail tokens.Accordingly, the total number of freedoms in coding tail tokens is288*8=2304.

Using, additionally, three transform types for tail tokens, the numberof contexts used to code tail tokens can be further reduced to 216(=3*2*2*3*6=3 transform sizes*2 plane types*2 reference types*3 bandpositions*6 coefficient contexts) resulting in an additional 12.5%reduction in contexts for coding tail tokens. Accordingly, the totalnumber of freedoms in coding tail tokens is 216*8=1728.

By reducing the number of freedoms for coding the tail tokens to 1728,the total number of freedoms (i.e., the number of stored probabilities)can be reduced to 4128 (=2304+96+1728) constituting a reduction of 41%(=(7008-4128)/7008) in stored probabilities.

FIG. 12 is a flowchart diagram of a process 1200 for coding a transformblock using a coefficient alphabet including head tokens and tail tokensaccording to an implementation of this disclosure. The process 1200 canbe implemented by an encoder such as the encoder 400 of FIG. 4. Whenimplemented by an encoder, coding means encoding in an encodedbitstream, such as the compressed bitstream 420 of FIG. 4. For example,the process 1200 can be performed in whole or in part by the entropyencoding stage 408 of the encoder 400. The process 1200 can be performedby a decoder such as the decoder 500 of FIG. 5. When implemented by adecoder, coding means decoding from an encoded bitstream, such as thecompressed bitstream 420 of FIG. 5. For example, the process 1200 can beperformed in whole or in part by the entropy decoding stage 502 of thedecoder 500 and the encoded video bitstream can be the compressedbitstream 420 of FIG. 5.

Implementations of the process 1200 can be performed by storinginstructions in a memory such as the memory 204 of the receiving station106 to be executed by a processor such as CPU 202, for example.

The process 1200 can be implemented using specialized hardware orfirmware. Some computing devices can have multiple memories, multipleprocessors, or both. The steps or operations of the process 1200 can bedistributed using different processors, memories, or both. Forsimplicity of explanation, the process 1200 is depicted and described asa series of steps or operations. However, the teachings in accordancewith this disclosure can occur in various orders and/or concurrently.Additionally, steps in accordance with this disclosure may occur withother steps not presented and described herein. Furthermore, not allillustrated steps or operations may be used to implement a method inaccordance with the disclosed subject matter.

At 1202, the process 1200 determines a head token for coding a transformcoefficient of the transform block. As used in this disclosure,“determine” means to select, construct, identify, specify, generate, orother determine in any manner whatsoever. For example, the process 1200can determine the token by traversing a coefficient token tree, such asthe coefficient token tree 700 of FIG. 7. In an example, the process1200 can determine that the head token is the TWO_PLUS_NEOB or the tokenTWO_PLUS_EOB.

At 1204, the process 1200 determines a tail token for coding thetransform coefficient. For example, 1100 can determine that the tailtoken is one of the tokens of the set of tail tokens as described above.For example, the process 1200 can determine the token by using the sametraversal of a coefficient token tree as that of 1202.

At 1206, the process 1200 determines a head context for coding the headtoken. The head context can be selected using one or more of a transformsize, a plane type, a reference type, a band position, and a coefficientcontext as described above. Other information can be available fordetermining the head context. In an example, and as described above, theprocess 1200 can determine that the head context is one of the 576contexts described above.

At 1208, the process 1200 determines a tail context for coding the tailtoken. The tail context can be selected using one or more of a transformsize, a plane type, a reference type, a band position, and a coefficientcontext as described above. Other information can be available fordetermining the head context. The tail context is selected from a set ofcontexts that includes less contexts than the set of contexts from whichthe head context is selected.

At 1210, the process 1200 codes the transform coefficient using the headtoken and the tail token.

In an implementation, the transform block is coded using a scandirection and the scan positions of the scan direction are mapped tofirst band positions having a first cardinality and second bandpositions having a second cardinality smaller than the firstcardinality. In an example, the first band positions can be {0, 1, 2, 3,4, 5}, which is a set having a cardinality of 6. In an example, thesecond band positions can be {0, 1, 2}, which is a set having acardinality of 3. The head context can be selected using the first bandpositions. The tail context can be selected using the second bandpositions.

In an implementation, the head context is selected using a head set oftransform sizes, the head set having a first cardinality and the tailcontext is selected using a tail set of transform sizes, the tail sethaving a second cardinality that is smaller than the first cardinality.In an example, the head set of transform sizes can be {TX_4X4, TX_8X8,TX_16X16, TX_32X32}, which has a cardinality of 4. In an example, thetail set of transform sizes can be {TX_4X4, TX_8X8, TX_16X16_ABOVE},which has a cardinality of 3.

As mentioned above, a codec can use backward-adaptivity or backwardupdates for entropy coding. As such, at the beginning of coding (i.e.,encoding and decoding) a frame (also referred to as an image) of videoor a portion of the frame (e.g., a tile), some or all of the probabilitydistributions to be used in entropy coding of the current frame and/ortile can be initialized. The probability distributions include binaryprobability distributions.

For example, the probability distributions for coding of theintra-prediction mode can be initialized. For example, the probabilitydistributions for coding the non-zero map (such as the non-zero map 706of FIG. 7) can be initialized. For example, the probabilitydistributions for coding the index of the scan positions groups can beinitialized. For example, when not coded using by-pass mode, theprobability distributions for coding significant bits of the offsetwithin the scan positions group can be initialized. For example, theprobability distributions for coding the end-of-block of a non-zero map,as described with respect to FIG. 9, can be initialized.

A binary probability distribution, for coding binary symbols (i.e., 0and 1 symbols), can be described and stored by using an N-bit value. Ina non-limiting example, and in a case where N=8, a probability value of1 can indicate that the symbol 0 has a probability of 1/256, and 128 canindicate that symbol 0 and symbol 1 have the same probability of128/256=0.5.

Implementations according to this disclosure can reduce the complexity(i.e., the number of bits) of storing and describing the initialprobability values. In some situations, such as the case of backwardadaptivity, a precise probability value is often not necessary becausethe probabilities are updated as the frame and/or tile are coded. Thatis, as a frame and/or tile is coded, an adaptation scheme adapts theinitial probabilities based on the statistics of the frame and/or tile.As such, using fewer bits to store the initial probability values doesnot necessarily result in any worse or better coding performance.

Implementations according to this disclosure can map an N-bit (e.g.,N=8) probability value to a smaller M-bit representation, where M<N isan integer number. The probability mapping can be such that theworst-case loss associated with mapping is a very small value. Theprobability mapping can be a non-uniform mapping that, given the initialprobabilities of a probability distribution, maps the probability space[0, 1] (if the probability is represented as a real number) or [1, 255](if the probability is represented as an integer number) intorepresentative values that can be stored in fewer bits than the initialprobability values.

FIG. 13 is a diagram of examples 1300 of probability mappings accordingto implementations of this disclosure. The probability mapping 1310 maps[1, 255] to 31 distinct values, which can be stored using 5 bits. Therow 1312, corresponding to an included LEFT LIMIT of 5 and an excludedRIGHT LIMIT of 8 (i.e., partition [5, 8)), indicates that probabilitiesin the set {5/256, 6/256, 7/256} are mapped to a single probability6/256 (as shown in the column REPRESENTATIVE PROBABILITY*256). The row1314 indicates that if an initial probability falls in the partition[40, 52), then the representative probability value of 45 is usedinstead.

When a probability p is mapped to another probability q, a loss incoding performance may result. The column labeled LOSS depicts theworst-case percentage loss due to using the mapping. For example, theworst-case loss associated with the rows 1312 and 1314 is 0.00367. Theloss associated with the row 1312 can described as follows: Using therepresentative probability 6, instead of any of the preciseprobabilities {5, 6, 7}, a maximum of 0.00367 additional bits may beused.

The loss is given by equation (3) as:

Loss=D(p∥q)/H(p)  (3)

In equation (3), D(p∥q) is the Kullback-Leibler (KL) divergence, definedon the same alphabet (e.g., the binary symbols 0 and 1), between thedistributions q and p, and H(p) denotes the entropy of the distribution(p, 1-p).

The KL divergence denotes the relative entropy between the twodistributions (p, 1-p) and (q, 1-q). The KL divergence is given byequation (4):

$\begin{matrix}{{D\left( p||q \right)} = {{p\log \frac{p}{q}} + {\left( {1 - p} \right)\log \frac{\left( {1 - p} \right)}{\left( {1 - q} \right)}}}} & (4)\end{matrix}$

The entropy H(p) can as given by equation (5):

H(p)=−p log p−(1 −p)log(1−p)  (5)

Given an initial probability distribution, a probability mapping can bedetermined in any number of ways. In an example, the probability mappingcan be determined using an exhaustive search algorithm that finds apartition composition (i.e., left and right limits for the partitions ofthe mapping) that meets a loss threshold for each partition or for themapping as a whole. That is, given the initial probability distributionsand a loss threshold as inputs, the search algorithm finds a suitablepartition of [1, 255] such that the representative probabilities of thepartitions minimize the cost for a given partition.

Minimizing the cost for a given partition means that the loss associatedwith the partition cannot be greater than the input loss threshold. Forexample, the input loss threshold used for generating the probabilitymapping 1310 is 0.6% and the search algorithm determined the partition[40, 52) (i.e., the row 1314) with a loss of 0.367%, which is smallerthan the loss threshold.

The search algorithm can proceed by finding a first partition that meetsthe loss threshold before proceeding to finding another partition. Thesearch algorithm can start the search at the top (e.g., starting with apartition that includes the LEFT LIMIT of 1), at the bottom (i.e.,starting with a partition that ends with the RIGHT LIMIT of 256), or atsome other partition.

Using the above mentioned search algorithm, and using a different lossthreshold, a probability mapping 1320 can be obtained such that [1,255]is mapped to 43 distinct values. In this example, loss is consistentlybelow 0.2%. The probability mapping 1320 can be stored using 6 bits. Thehigher the number of partitions in the probability mapping, the smallerthe loss.

Probability mapping 1330 is yet another example of mapping [1, 255]using another loss threshold. The probability mapping includes 15distinct values (i.e., 15 partitions). As such, 4 bits are required tostore the values of the probability mapping 1330.

In some implementations, an encoder encodes initial probabilitydistributions in an encoded bitstream, such as in the header of a frame,and a decoder decodes the initial probability distributions from theencoded bitstream. Using probability mapping as described above, thenumber of bits required to transmit the initial distributions can bereduced. In some cases, the reduction can be significant, such as whenthe frame is significantly compressed.

Probability mappings can be used to signal probability values inbackward updates of probabilities or to describe initial probabilityvalues to use at the start of coding (encoding or decoding) a picture(i.e., frame) or a tile of a frame.

As mentioned above, a current block can be predicted using intraprediction. An intra prediction mode uses pixels peripheral to thecurrent block being predicted. Pixels peripheral to the current blockare pixels outside the current block. Many different intra predictionmodes can be available. Some intra prediction modes use a single valuefor all pixels within the prediction block generated using at least oneof the peripheral pixels. Other intra prediction modes, which may bereferred to as directional intra prediction modes, each can have acorresponding prediction angle. Other types of intra prediction modescan also be available.

An intra prediction mode may be selected by the encoder as part of arate distortion loop. In brief, various intra prediction modes may betested to determine which type of prediction will have the lowestdistortion for a given rate, or number of bits to be transmitted in anencoded video bitstream, including overhead bits included in thebitstream to indicate the type of prediction used.

In an example, the following 13 intra prediction modes can be available:DC_PRED, V_PRED, H_PRED, D45_PRED, D135_PRED, D117_PRED, D153_PRED,D207_PRED, D63_PRED, SMOOTH_PRED, SMOOTH_V_PRED, and SMOOTH_H_PRED, andPAETH_PRED. One of the 13 intra prediction modes can be used to predicta luminance block.

FIG. 14 is a diagram of examples of intra prediction modes according toimplementations of this disclosure. Intra prediction mode 1410illustrates the V_PRED intra prediction mode, which is referred togenerally as a vertical intra prediction mode. In this mode, predictionblock pixels in the first column are set to the value of peripheralpixel A; prediction block pixels in the second column are set to thevalue of pixel B; prediction block pixels in the third column are set tothe value of pixel C; and prediction block pixels in the fourth columnare set to the value of pixel D.

Intra prediction mode 1420 illustrates the H_PRED intra prediction mode,which is referred to generally as a horizontal intra prediction mode. Inthis mode, prediction block pixels in the first row are set to the valueof peripheral pixel I; prediction block pixels in the second row are setto the value of pixel J; prediction block pixels in the third row areset to the value of pixel K; and prediction block pixels in the fourthrow are set to the value of pixel L.

Intra prediction mode 1430 illustrates the D117_PRED intra predictionmode, so-called because the direction of the arrows, along which theperipheral pixels will be propagated to generate the prediction blockform a diagonal, is at an angle of about 117° from the horizontal. Thatis, in the D117_PRED, the prediction angle is 117°. Intra predictionmode 1440 illustrates the D63_PRED intra prediction mode, whichcorresponds to a prediction angle of 63°. Intra prediction mode 1450illustrates the D153_PRED intra prediction mode, which corresponds to aprediction angle of 153°. Intra prediction mode 1460 illustrates theD135_PRED intra prediction mode, which corresponds to a prediction angleof 135°.

The prediction modes D45_PRED and D207_PRED (not shown) correspond,respectively, to the prediction angles 45° and 207°. DC_PRED correspondsto a prediction mode where all prediction block pixels are set to asingle value that is a combination of the peripheral pixels A-M.

In the PAETH_PRED intra prediction mode, the prediction value of a pixelis determined as follows: 1) calculate a base value as a combination ofsome peripheral pixels, and 2) use, as the prediction pixel, the one ofthe some peripheral pixels that is closest to the base value. ThePAETH_PRED intra prediction mode is illustrated using, as an example, apixel 1412 (at location x=1, y=2). In an example of a combination ofsome peripheral pixels, the base value can calculated as base=B+K−M.That is, the base value is equal to: the value of the left peripheralpixel that is in the same row as the pixel to be predicted + the valueof the above peripheral pixel that is in the same column as the pixel −the value of the pixel in the top-left corner.

In the SMOOTH_V intra prediction mode, the prediction pixels of thebottom-most row of the prediction block are estimated with the value ofthe last pixel in the left column (i e, the value of pixel at locationL). The remaining pixels of the prediction block are calculated byquadratic interpolation in the vertical direction.

In the SMOOTH_H intra prediction mode, the prediction pixels of theright-most column of the prediction block are estimated with the valueof the last pixel in the top row (i.e., the value of pixel at locationD). The remaining pixels of the prediction block are calculated byquadratic interpolation in the horizontal direction.

In the SMOOTH_PRED intra prediction mode, the prediction pixels of thebottom-most row of the prediction block are estimated with the value ofthe last pixel in the left column (i.e., the value of pixel at locationL) and the prediction pixels of the right-most column of the predictionblock are estimated with the value of the last pixel in the top row(i.e., the value of pixel at location D). The remaining pixels of theprediction block are calculated as scaled weighted sums. For example,the value of a prediction pixel at location (i, j) of the predictionblock can be calculated as the scaled weighted sum of the values ofpixels L_(j), R, T_(i), and B. The pixel L_(j) is a pixel in the leftcolumn and on the same row as the prediction pixel. The pixel R is thepixel as provided by SMOOTH_H. The pixel T_(i) is a pixel in the aboverow and on the same column as the prediction pixel. The pixel B is thepixel as provided by SMOOTH_V. The weights can be equivalent to aquadratic interpolation in the horizontal and vertical directions.

The intra prediction mode selected by the encoder can be transmitted toa decoder in the bitstream. The intra prediction mode can be entropycoded (encoded by the encoder and/or decoded by a decoder) using acontext model.

Some codecs use the intra prediction modes of the left and aboveneighbor blocks as the context for coding the intra prediction mode of acurrent block. Using FIG. 14 as an example, the left neighbor block canbe the block containing the pixels I-L, and the above neighbor block canbe the block containing the pixels A-D.

A codec can include a probability distribution for each combination ofintra prediction modes used by the left neighbor block and aboveneighbor block. As such, using the above 13 prediction modes, 169probability distributions (corresponding to 13*13=169 contexts) may arestored. To retrieve a probability distribution, the codec can perform aprocedure that includes the steps:

cdf_prob kf_y_mode_cdf [13] [13] [13] ; left = left neighbor intra mode(or DC_PRED if unavailable) above = above neighbor intra mode (orDC_PRED if unavailable) prob_table = kf_y_mode_cdf [left] [above] ;

For ease of reference, the above procedure is referred as thectx-combinations technique. In the ctx-combinations technique, leftstores the intra prediction mode of the left neighbor block. If theintra prediction mode of the left neighbor block is not available, thenthe DC-PRED intra prediction more may be assumed. Above stores the intraprediction mode of the top neighbor block. If the intra prediction modeof the above neighbor block is not available, then the DC-PRED intraprediction mode may be assumed.

An intra prediction mode may not be available because, for example, thecurrent block is at the edge (e.g., top-most and/or left-most block) ofthe frame or the neighbor block (left or above) was inter-predicted. Theintra prediction mode may not be available for other reasons. Theprobability distribution (i.e., prob_table) can be retrieved from athree-dimensional array (i.e., kf_y_mode_cdf) that includes theprobability distributions for all combinations of left and above intraprediction modes. In an example, the first dimension corresponds to theleft neighbor intra prediction mode (e.g., 13 values), the seconddimension corresponds to the above neighbor intra prediction mode (e.g.,13 values), and the third dimension corresponds to the values of aprobability distribution.

As indicated above, each probability distribution includes 13probability values (i.e., a probability value for each of the predictionmodes). As such, there are 12 freedoms (i.e., only 12 of the 13probability values are stored per context). In some implementations, a13th entry that is a constant (e.g., a 0) may also be stored.

The number of stored probability distributions and/or probability valuesper probability distribution can be reduced by reducing the number ofcontexts for coding an intra prediction mode.

In an example, the number of contexts can be reduced when some of theintra prediction modes exhibit certain characteristics. For example, theprobabilities of some of the intra prediction modes may notsignificantly change based on the left intra prediction mode and/or theabove intra prediction mode. Such intra prediction modes may be equallyprobable regardless of the left and above intra prediction modes. In anexample, the SMOOTH_PRED, SMOOTH_V_PRED, and SMOOTH_H_PRED predictionmodes may exhibit such characteristics.

Implementations according to this disclosure can reduce the number ofcontexts available for coding the intra prediction mode of a currentblock using a procedure that includes the steps:

1. cdf_prob kf_y_mode_cdf [13] [2] [13] ; 2. left = left neighbor intramode (or DC_PRED if unavailable) 3. above = above neighbor intra mode(or DC_PRED if unavailable) 4. if (left == above)  a. prob_table =kf_y_mode_cdf [left] [0] ; 5. else if (left != SMOOTH_PRED && left !=SMOOTH_H_PRED &&   left != SMOOTH_V_PRED)  a. prob_table = kf_y_mode_cdf[left] [1] ; 6. else  a. prob_table = kf_y_mode_cdf [above] [1] ;

For ease of reference, the above procedure is referred to as thefirst-ctx-reduction technique. Using the first-ctx-reduction technique,the number of contexts can be reduced to 26. As such, the number ofcontexts used to code (encode/decode) the intra prediction modes ofluminance blocks can be reduced by approximately 85%. In the steps 4-4aabove, if the left neighbor block and the above neighbor block use thesame intra prediction mode, then the left intra prediction mode is usedto retrieve a probability distribution. This accounts for 13 probabilitydistributions. The steps 5-6 can be summarized as: if one of left orabove neighbors uses a smooth prediction mode (i.e., one of SMOOTH_PRED,SMOOTH_V_PRED, or SMOOTH_H_PRED), then retrieve a probabilitydistribution using the other intra prediction mode. These steps accountfor another 13 probability distributions.

In an implementation, the steps can be used to determine the context forcoding the intra-prediction modes of blocks of keys frame (also known asgolden frame). In a key frame, all blocks are predicted using intraprediction.

FIG. 15 is a flowchart diagram of a process 1500 for intra-coding acurrent block according to an implementation of this disclosure. Theprocess 1500 can be implemented by an encoder such as the encoder 400 ofFIG. 4. When implemented by an encoder, coding means encoding in anencoded bitstream, such as the compressed bitstream 420 of FIG. 4. Forexample, the process 1500 can be performed in whole or in part by theentropy encoding stage 408 of the encoder 400. The process 1500 can beperformed by a decoder such as the decoder 500 of FIG. 5. Whenimplemented by a decoder, coding means decoding from an encodedbitstream, such as the compressed bitstream 420 of FIG. 5. For example,the process 1500 can be performed in whole or in part by the entropydecoding stage 502 of the decoder 500 and the encoded video bitstreamcan be the compressed bitstream 420 of FIG. 5.

Implementations of the process 1500 can be performed by storinginstructions in a memory such as the memory 204 of the receiving station106 to be executed by a processor such as CPU 202, for example.

The process 1500 can be implemented using specialized hardware orfirmware. Some computing devices can have multiple memories, multipleprocessors, or both. The steps or operations of the process 1500 can bedistributed using different processors, memories, or both. Forsimplicity of explanation, the process 1500 is depicted and described asa series of steps or operations. However, the teachings in accordancewith this disclosure can occur in various orders and/or concurrently.Additionally, steps in accordance with this disclosure may occur withother steps not presented and described herein. Furthermore, not allillustrated steps or operations may be used to implement a method inaccordance with the disclosed subject matter.

At 1502, the process 1500 codes the current block using anintra-prediction mode. At 1504, the process 1500 determines a leftintra-mode (i.e., an intra prediction mode) of a left neighbor block. Inan implementation, if the left intra-mode is not available, then theleft intra-mode is assumed to be the DC_PRED mode. At 1506, the process1500 determines an above intra-mode (i.e., an intra prediction mode) ofan above neighbor block. In an implementation, if the above intra-modeis not available, then the above intra-mode is assumed to be the DC_PREDmode.

At 1510, if the left intra-mode and the above intra-mode are the same,then the process 1500 proceeds to 1512; otherwise the process 1500proceeds to 1516. At 1512, the process 1500 uses one of the leftintra-mode or the above intra-mode (which are the same) to determine aprobability distribution for coding the intra-prediction mode. As such,on condition that the left intra-mode and the above intra-mode beingequal to a same mode, using the same mode to determine a probabilitydistribution for coding the intra-prediction mode. As used in thisdisclosure, “determine” means to select, construct, identify, specify,generate, or other determine in any manner whatsoever. For example, theprobability distribution can be retrieved from a memory.

At 1516, on condition that one of the left intra-mode or the aboveintra-mode being a smooth mode, the process 1500 use the other of theleft intra-mode and the above intra-mode to determine the probabilitydistribution for coding the intra-prediction mode. In an implementation,the smooth mode can be one of SMOOTH_PRED, SMOOTH_H_PRED, andSMOOTH_V_PRED. At 1514, the process 1500 codes the intra-prediction modeusing the probability distribution.

The number of contexts for coding the intra prediction mode of a currentcan be reduced by splitting the available intra prediction modes intoclasses. Each class can include one or more intra prediction modes. Thenumber of symbols coded for an intra prediction mode can depend on theclass of the intra prediction mode.

In an example, the 13 intra prediction modes described above can besplit into classes as shown in Table II.

TABLE II Intra Prediction Mode Intra Prediction Class DC_PRED DC H_PREDH V_PRED V SMOOTH_PRED, SMOOTH_V_PRED, and SMOOTH SMOOTH_H_PREDPAETH_PRED PAETH D45_PRED, D135_PRED, D117_PRED, OTHER D153_PRED,D207_PRED, D63_PRED

A first symbol can indicate the intra prediction class of the intraprediction mode. As there are six (6) intra prediction classes in TableII, using the ctx-combinations technique for determining a probabilitydistribution for coding the first symbol, a total of 36 contexts arepossible. The 36 contexts corresponding to six (6) possible classes forthe left neighbor block and six (6) possible classes for the aboveneighbor class. Each of contexts includes five (5) probability values.Using the first-ctx-reduction technique, only 12 (=6*2) contexts arerequired to code the first symbol.

If the intra prediction mode is in the class SMOOTH, then using thectx-combinations technique for determining a probability distributionfor coding a second symbol, a total of nine (9) contexts are possible.The nine (9) contexts corresponding to three (3) possible smooth intraprediction modes for the left neighbor block and three (3) possiblesmooth intra prediction modes for the above neighbor class. Using thefirst-ctx-reduction technique, only one (1) context is required. Eachcontext includes 2 probability values.

If the intra prediction mode is in the class OTHER, then using thectx-combinations technique for determining a probability distributionfor coding the second symbol, a total of 36 contexts are possible. The36 contexts corresponding to six (6) possible intra prediction modes inthe OTHER class for the left neighbor block and six (6) possible intraprediction modes in the OTHER class for the above neighbor class. Usingthe first-ctx-reduction technique, only 12 contexts are required. Eachcontext provides five (5) probability values.

For simplicity of explanation, the processes 600, 900, 1200, 1500, and1700 are each depicted and described as a series of blocks, steps, oroperations. However, the blocks, steps, or operations in accordance withthis disclosure can occur in various orders and/or concurrently.Additionally, other steps or operations not presented and describedherein may be used. Furthermore, not all illustrated steps or operationsmay be required to implement a technique in accordance with thedisclosed subject matter.

The aspects of encoding and decoding described above illustrate someencoding and decoding techniques. However, it is to be understood thatencoding and decoding, as those terms are used in the claims, could meancompression, decompression, transformation, or any other processing orchange of data.

The words “example” or “implementation” are used herein to mean servingas an example, instance, or illustration. Any aspect or design describedherein as “example” or “implementation” is not necessarily to beconstrued as preferred or advantageous over other aspects or designs.Rather, use of the words “example” or “implementation” is intended topresent concepts in a concrete fashion. As used in this application, theterm “or” is intended to mean an inclusive “or” rather than an exclusive“or”. That is, unless specified otherwise, or clear from context, “Xincludes A or B” is intended to mean any of the natural inclusivepermutations. That is, if X includes A; X includes B; or X includes bothA and B, then “X includes A or B” is satisfied under any of theforegoing instances. In addition, the articles “a” and “an” as used inthis application and the appended claims should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form. Moreover, use of the term “animplementation” or “one implementation” throughout is not intended tomean the same embodiment or implementation unless described as such.

Implementations of transmitting station 102 and/or receiving station 106(and the algorithms, methods, instructions, etc., stored thereon and/orexecuted thereby, including by encoder 400 and decoder 500) can berealized in hardware, software, or any combination thereof. The hardwarecan include, for example, computers, intellectual property (IP) cores,application-specific integrated circuits (ASICs), programmable logicarrays, optical processors, programmable logic controllers, microcode,microcontrollers, servers, microprocessors, digital signal processors orany other suitable circuit. In the claims, the term “processor” shouldbe understood as encompassing any of the foregoing hardware, eithersingly or in combination. The terms “signal” and “data” are usedinterchangeably. Further, portions of transmitting station 102 andreceiving station 106 do not necessarily have to be implemented in thesame manner.

Further, in one aspect, for example, transmitting station 102 orreceiving station 106 can be implemented using a general-purposecomputer or general-purpose processor with a computer program that, whenexecuted, carries out any of the respective methods, algorithms and/orinstructions described herein. In addition, or alternatively, forexample, a special purpose computer/processor can be utilized which cancontain other hardware for carrying out any of the methods, algorithms,or instructions described herein.

Transmitting station 102 and receiving station 106 can, for example, beimplemented on computers in a video conferencing system. Alternatively,transmitting station 102 can be implemented on a server and receivingstation 106 can be implemented on a device separate from the server,such as a hand-held communications device. In this instance,transmitting station 102 can encode content using an encoder 400 into anencoded video signal and transmit the encoded video signal to thecommunications device. In turn, the communications device can thendecode the encoded video signal using a decoder 500. Alternatively, thecommunications device can decode content stored locally on thecommunications device, for example, content that was not transmitted bytransmitting station 102. Other transmitting station 102 and receivingstation 106 implementation schemes are available. For example, receivingstation 106 can be a generally stationary personal computer rather thana portable communications device and/or a device including an encoder400 may also include a decoder 500.

Further, all or a portion of implementations of the present disclosurecan take the form of a computer program product accessible from, forexample, a tangible computer-usable or computer-readable medium. Acomputer-usable or computer-readable medium can be any device that can,for example, tangibly contain, store, communicate, or transport theprogram for use by or in connection with any processor. The medium canbe, for example, an electronic, magnetic, optical, electromagnetic, or asemiconductor device. Other suitable mediums are also available.

The above-described embodiments, implementations and aspects have beendescribed in order to allow easy understanding of the present disclosureand do not limit the present disclosure. On the contrary, the disclosureis intended to cover various modifications and equivalent arrangementsincluded within the scope of the appended claims, which scope is to beaccorded the broadest interpretation so as to encompass all suchmodifications and equivalent structure as is permitted under the law.

What is claimed is:
 1. An apparatus for decoding a current block,comprising: a processor configured to: obtain a transform class of atransform type used for decoding a transform block of the current block;select, based on the transform class, a template for coding a valuerelated to a transform coefficient at a row and a column of thetransform block; obtain, using the template, an index of a probabilitydistribution in a table of probability distributions; and decode, from acompressed bitstream, the value using the probability distribution. 2.The apparatus of claim 1, wherein the transform class is one of avertical transform class (TX_CLASS_VERT), a horizontal transform class(TX_CLASS_HORIZ), or a 2-dimensional transform class (TX_CLASS_2D). 3.The apparatus of claim 2, wherein each of the vertical transform class,the horizontal transform class, and the 2-dimensional transform classmaps to a respective distinct index.
 4. The apparatus of claim 2,wherein the vertical transform class and the horizontal transform classmap to a first index in the table of probability distributions, and the2-dimensional transform class maps to a second index in the table ofprobability distributions, wherein the first index and the second indexare used to obtain the index of the probability distribution.
 5. Theapparatus of claim 1, wherein the index of the probability distributionis equal to zero in a case that the row is zero and the column is zero.6. The apparatus of claim 1, wherein to obtain, using the template, theindex of the probability distribution in the table of probabilitydistributions comprises to: obtain an aggregate of respective valuescorresponding to locations of the template; and use the aggregate of therespective values to obtain the index of the probability distribution.7. The apparatus of claim 6, wherein the aggregate of the respectivevalues is a count of non-zero values of the respective valuescorresponding to the locations of the template.
 8. The apparatus ofclaim 6, wherein the aggregate of the respective values is a sum of therespective values corresponding to the locations of the template.
 9. Amethod for coding a current block, comprising: obtaining a transformclass of a transform type used for decoding a transform block of thecurrent block; selecting, based on the transform class, a template forcoding a value related to a transform coefficient at a row and a columnof the transform block; obtaining, using the template, an index of aprobability distribution in a table of probability distributions; andcoding the value using the probability distribution.
 10. The method ofclaim 9, wherein the transform class is one of a vertical transformclass (TX_CLASS_VERT), a horizontal transform class (TX_CLASS_HORIZ), ora 2-dimensional transform class (TX_CLASS_2D).
 11. The method of claim10, wherein each of the vertical transform class, the horizontaltransform class, and the 2-dimensional transform class maps to arespective distinct index.
 12. The method of claim 10, wherein thevertical transform class and the horizontal transform class map to afirst index in the table of probability distributions, and the2-dimensional transform class maps to a second index in the table ofprobability distributions, wherein the first index and the second indexare used to obtain the index of the probability distribution.
 13. Themethod of claim 9, wherein the index of the probability distribution isequal to zero in a case that the row is zero and the column is zero. 14.The method of claim 9, wherein obtaining, using the template, the indexof the probability distribution in the table of probabilitydistributions comprises: obtaining an aggregate of respective valuescorresponding to locations of the template; and using the aggregate ofthe respective values to obtain the index of the probabilitydistribution.
 15. The method of claim 14, wherein the aggregate of therespective values is a count of non-zero values of the respective valuescorresponding to the locations of the template.
 16. The method of claim15, wherein the aggregate of the respective values is a sum of therespective values corresponding to the locations of the template. 17.The method of claim 9, wherein coding the value using the probabilitydistribution comprises: decoding the value from a compressed bitstreamusing the probability distribution.
 18. The method of claim 9, whereincoding the value using the probability distribution comprises: encodingthe value in a compressed bitstream using the probability distribution19. A non-transitory computer-readable storage medium, comprisingexecutable instructions that, when executed, facilitate performance ofoperations for coding a current block, the operations comprising to:obtain a transform class of a transform type used for decoding atransform block of the current block, wherein the transform class is oneof a vertical transform class, a horizontal transform class, or a2-dimensional transform class; select, based on the transform class, atemplate for coding a value related to a transform coefficient at a rowand a column of the transform block; obtain, using the template, anindex of a probability distribution in a table of probabilitydistributions; and decode, from a compressed bitstream, the value usingthe probability distribution.
 20. The non-transitory computer-readablestorage medium of claim 19, wherein the vertical transform class and thehorizontal transform class map to a first index in the table ofprobability distributions, and the 2-dimensional transform class maps toa second index in the table of probability distributions, wherein thefirst index and the second index are used to obtain the index of theprobability distribution.